Package 'fastNaiveBayes' reference manual

Title:	Extremely Fast Implementation of a Naive Bayes Classifier
Description:	This is an extremely fast implementation of a Naive Bayes classifier. This package is currently the only package that supports a Bernoulli distribution, a Multinomial distribution, and a Gaussian distribution, making it suitable for both binary features, frequency counts, and numerical features. Another feature is the support of a mix of different event models. Only numerical variables are allowed, however, categorical variables can be transformed into dummies and used with the Bernoulli distribution. The implementation is largely based on the paper "A comparison of event models for Naive Bayes anti-spam e-mail filtering" written by K.M. Schneider (2003) <doi:10.3115/1067807.1067848>. Any issues can be submitted to: <https://github.com/mskogholt/fastNaiveBayes/issues>.
Authors:	Martin Skogholt
Maintainer:	Martin Skogholt <[email protected]>
License:	GPL-3
Version:	2.2.1
Built:	2025-02-19 04:59:48 UTC
Source:	https://github.com/mskogholt/fastnaivebayes

Fast Naive Bayes Classifier for different Distributions

Description

Extremely fast implementation of a Naive Bayes Classifier.

A Naive Bayes classifier that assumes independence between the feature variables. Currently, either a Bernoulli, multinomial, or Gaussian distribution can be used. The bernoulli distribution should be used when the features are 0 or 1 to indicate the presence or absence of the feature in each document. The multinomial distribution should be used when the features are the frequency that the feature occurs in each document. Finally, the Gaussian distribution should be used with numerical variables. The distribution parameter is used to mix different distributions for different columns in the input matrix

Use fastNaiveBayes(...) or fnb.train(...) for a mixed event distribution model. fnb.bernoulli, fnb.multinomial, fnb.gaussian and for the specific distributions

Usage

fastNaiveBayes(
  x,
  y,
  priors = NULL,
  laplace = 0,
  sparse = FALSE,
  check = TRUE,
  distribution = fnb.detect_distribution(x)
)

## Default S3 method:
fastNaiveBayes(
  x,
  y,
  priors = NULL,
  laplace = 0,
  sparse = FALSE,
  check = TRUE,
  distribution = fnb.detect_distribution(x)
)

fnb.bernoulli(x, y, priors = NULL, laplace = 0, sparse = FALSE, check = TRUE)

## Default S3 method:
fnb.bernoulli(x, y, priors = NULL, laplace = 0, sparse = FALSE, check = TRUE)

fnb.gaussian(x, y, priors = NULL, sparse = FALSE, check = TRUE)

## Default S3 method:
fnb.gaussian(x, y, priors = NULL, sparse = FALSE, check = TRUE)

fnb.multinomial(x, y, priors = NULL, laplace = 0, sparse = FALSE, check = TRUE)

## Default S3 method:
fnb.multinomial(x, y, priors = NULL, laplace = 0, sparse = FALSE, check = TRUE)

fnb.poisson(x, y, priors = NULL, sparse = FALSE, check = TRUE)

## Default S3 method:
fnb.poisson(x, y, priors = NULL, sparse = FALSE, check = TRUE)

fnb.train(
  x,
  y,
  priors = NULL,
  laplace = 0,
  sparse = FALSE,
  check = TRUE,
  distribution = fnb.detect_distribution(x)
)

## Default S3 method:
fnb.train(
  x,
  y,
  priors = NULL,
  laplace = 0,
  sparse = FALSE,
  check = TRUE,
  distribution = fnb.detect_distribution(x)
)
fastNaiveBayes(
  x,
  y,
  priors = NULL,
  laplace = 0,
  sparse = FALSE,
  check = TRUE,
  distribution = fnb.detect_distribution(x)
)

## Default S3 method:
fastNaiveBayes(
  x,
  y,
  priors = NULL,
  laplace = 0,
  sparse = FALSE,
  check = TRUE,
  distribution = fnb.detect_distribution(x)
)

fnb.bernoulli(x, y, priors = NULL, laplace = 0, sparse = FALSE, check = TRUE)

## Default S3 method:
fnb.bernoulli(x, y, priors = NULL, laplace = 0, sparse = FALSE, check = TRUE)

fnb.gaussian(x, y, priors = NULL, sparse = FALSE, check = TRUE)

## Default S3 method:
fnb.gaussian(x, y, priors = NULL, sparse = FALSE, check = TRUE)

fnb.multinomial(x, y, priors = NULL, laplace = 0, sparse = FALSE, check = TRUE)

## Default S3 method:
fnb.multinomial(x, y, priors = NULL, laplace = 0, sparse = FALSE, check = TRUE)

fnb.poisson(x, y, priors = NULL, sparse = FALSE, check = TRUE)

## Default S3 method:
fnb.poisson(x, y, priors = NULL, sparse = FALSE, check = TRUE)

fnb.train(
  x,
  y,
  priors = NULL,
  laplace = 0,
  sparse = FALSE,
  check = TRUE,
  distribution = fnb.detect_distribution(x)
)

## Default S3 method:
fnb.train(
  x,
  y,
  priors = NULL,
  laplace = 0,
  sparse = FALSE,
  check = TRUE,
  distribution = fnb.detect_distribution(x)
)

Arguments

`x`	a numeric matrix, or a dgcMatrix. For bernoulli should only contain 0's and 1's. For multinomial should only contain integers.
`y`	a factor of classes to classify
`priors`	a numeric vector with the priors. If left empty the priors will be determined by the relative frequency of the classes in the data
`laplace`	A number used for Laplace smoothing. Default is 0
`sparse`	Use a sparse matrix? If true a sparse matrix will be constructed from x. It's possible to directly feed a sparse dgcMatrix as x, which will set this parameter to TRUE
`check`	Whether to enable formal checks on input. Recommended to set to TRUE. Set to FALSE will make it faster, but at your own risk.
`distribution`	A list with distribution names and column names for which to use the distribution, see examples.

Details

fastNaiveBayes(...) will convert non numeric columns to one hot encoded features to use with the Bernoulli event model. NA's in x will be set to 0 by default and observations with NA in y will be removed.

The distribution that is used for each feature is determined by a set of rules: - if the column only contains 0's and 1's a Bernoulli event model will be used - if the column only contains whole numbers a Multinomial event model will be used - if none of the above a Gaussian event model will be used.

By setting sparse = TRUE the numeric matrix x will be converted to a sparse dgcMatrix. This can be considerably faster in case few observations have a value different than 0.

It's also possible to directly supply a sparse dgcMatrix, which can be a lot faster in case a fastNaiveBayes model is trained multiple times on the same matrix or a subset of this. See examples for more details. Bear in mind that converting to a sparse matrix can actually be slower depending on the data.

Value

A fitted object of class "fastNaiveBayes". It has four components:

model: Fitted fastNaiveBayes model
names: Names of features used to train this fastNaiveBayes model
distribution: Distribution used for each column of x
levels: Levels of y

Examples

rm(list = ls())
library(fastNaiveBayes)
cars <- mtcars
y <- as.factor(ifelse(cars$mpg > 25, "High", "Low"))
x <- cars[,2:ncol(cars)]

mod <- fastNaiveBayes(x, y, laplace = 1)

pred <- predict(mod, newdata = x)
mean(y!=pred)

mod <- fnb.train(x, y, laplace = 1)

pred <- predict(mod, newdata = x)
mean(y!=pred)

dist <- fnb.detect_distribution(x)

bern <- fnb.bernoulli(x[,dist$bernoulli], y, laplace = 1)
pred <- predict(bern, x[,dist$bernoulli])
mean(y!=pred)

mult <- fnb.multinomial(x[,dist$multinomial], y, laplace = 1)
pred <- predict(mult, x[,dist$multinomial])
mean(y!=pred)

gauss <- fnb.gaussian(x[,dist$gaussian], y)
pred <- predict(gauss, x[,dist$gaussian])
mean(y!=pred)

rm(list = ls())
library(fastNaiveBayes)
cars <- mtcars
y <- as.factor(ifelse(cars$mpg > 25, "High", "Low"))
x <- cars[,2:ncol(cars)]

mod <- fastNaiveBayes(x, y, laplace = 1)

pred <- predict(mod, newdata = x)
mean(y!=pred)

mod <- fnb.train(x, y, laplace = 1)

pred <- predict(mod, newdata = x)
mean(y!=pred)

dist <- fnb.detect_distribution(x)

bern <- fnb.bernoulli(x[,dist$bernoulli], y, laplace = 1)
pred <- predict(bern, x[,dist$bernoulli])
mean(y!=pred)

mult <- fnb.multinomial(x[,dist$multinomial], y, laplace = 1)
pred <- predict(mult, x[,dist$multinomial])
mean(y!=pred)

gauss <- fnb.gaussian(x[,dist$gaussian], y)
pred <- predict(gauss, x[,dist$gaussian])
mean(y!=pred)

Distribution Detection Function

Description

Determines which distribution to use for which columns in the matrix based on a set of rules.

Usage

fnb.detect_distribution(x, nrows = nrow(x))

## Default S3 method:
fnb.detect_distribution(x, nrows = nrow(x))
fnb.detect_distribution(x, nrows = nrow(x))

## Default S3 method:
fnb.detect_distribution(x, nrows = nrow(x))

Arguments

`x`	a numeric matrix, or a dgcMatrix
`nrows`	number of rows to use to detect distributions

Details

A simple utility function to detect the distribution to use for each columns

Value

A list of distribution names mapped to column names

Examples

rm(list = ls())
library(fastNaiveBayes)
cars <- mtcars
y <- as.factor(ifelse(cars$mpg > 25, "High", "Low"))
x <- cars[, 2:ncol(cars)]

# Uses default of all rows to determine distributions
dist <- fnb.detect_distribution(x)
print(dist)

# Uses top 10 rows of x to determine distributions. If top 10 rows
# are representative this is can be much faster.
dist <- fnb.detect_distribution(x, nrows = 10)
print(dist)
rm(list = ls())
library(fastNaiveBayes)
cars <- mtcars
y <- as.factor(ifelse(cars$mpg > 25, "High", "Low"))
x <- cars[, 2:ncol(cars)]

# Uses default of all rows to determine distributions
dist <- fnb.detect_distribution(x)
print(dist)

# Uses top 10 rows of x to determine distributions. If top 10 rows
# are representative this is can be much faster.
dist <- fnb.detect_distribution(x, nrows = 10)
print(dist)

Save & Load Function for Fast Naive Bayes Models

Description

Loads and saves fitted Naive Bayes models.

Usage

fnb.save(model, filename, overwrite = FALSE)

## Default S3 method:
fnb.save(model, filename, overwrite = FALSE)

fnb.load(filename)

## Default S3 method:
fnb.load(filename)
fnb.save(model, filename, overwrite = FALSE)

## Default S3 method:
fnb.save(model, filename, overwrite = FALSE)

fnb.load(filename)

## Default S3 method:
fnb.load(filename)

Arguments

`model`	the fitted Naive Bayes model to save.
`filename`	the file name to use to save or load the model.
`overwrite`	Whether to allow overwriting of previously saved models.

Value

fnb.save returns the filename that was used, and fnb.load returns the saved object.

Examples

rm(list = ls())
library(fastNaiveBayes)
cars <- mtcars
y <- as.factor(ifelse(cars$mpg > 25, "High", "Low"))
x <- cars[,2:ncol(cars)]

mod <- fastNaiveBayes(x, y, laplace = 1)
fnb.save(mod, "fastNaiveBayesModel")
mod2 <- fnb.load("fastNaiveBayesModel")
identical(mod, mod2)
file.remove("fastNaiveBayesModel")

rm(list = ls())
library(fastNaiveBayes)
cars <- mtcars
y <- as.factor(ifelse(cars$mpg > 25, "High", "Low"))
x <- cars[,2:ncol(cars)]

mod <- fastNaiveBayes(x, y, laplace = 1)
fnb.save(mod, "fastNaiveBayesModel")
mod2 <- fnb.load("fastNaiveBayesModel")
identical(mod, mod2)
file.remove("fastNaiveBayesModel")

Update function

Description

Update function

Usage

fnb.update(object, x, y, sparse = FALSE, check = TRUE)

## Default S3 method:
fnb.update(object, x, y, sparse = FALSE, check = TRUE)

## S3 method for class 'fnb.bernoulli'
fnb.update(object, x, y, sparse = FALSE, check = TRUE)

## S3 method for class 'fnb.multinomial'
fnb.update(object, x, y, sparse = FALSE, check = TRUE)

## S3 method for class 'fnb.gaussian'
fnb.update(object, x, y, sparse = FALSE, check = TRUE)

## S3 method for class 'fnb.poisson'
fnb.update(object, x, y, sparse = FALSE, check = TRUE)

## S3 method for class 'fastNaiveBayes'
fnb.update(object, x, y, sparse = FALSE, check = TRUE)
fnb.update(object, x, y, sparse = FALSE, check = TRUE)

## Default S3 method:
fnb.update(object, x, y, sparse = FALSE, check = TRUE)

## S3 method for class 'fnb.bernoulli'
fnb.update(object, x, y, sparse = FALSE, check = TRUE)

## S3 method for class 'fnb.multinomial'
fnb.update(object, x, y, sparse = FALSE, check = TRUE)

## S3 method for class 'fnb.gaussian'
fnb.update(object, x, y, sparse = FALSE, check = TRUE)

## S3 method for class 'fnb.poisson'
fnb.update(object, x, y, sparse = FALSE, check = TRUE)

## S3 method for class 'fastNaiveBayes'
fnb.update(object, x, y, sparse = FALSE, check = TRUE)

Arguments

`object`	fitted model
`x`	numeric matrix
`y`	factor of classes
`sparse`	boolean, set to true to use sparse matrices
`check`	boolean, set to true to enable formal checks on input

Predict Method for fastNaiveBayes fits

Description

Uses a fastNaiveBayes model and a new data set to create the classifications. This can either be the raw probabilities generated by the fastNaiveBayes model or the classes themselves.

Usage

## S3 method for class 'fnb.bernoulli'
predict(
  object,
  newdata,
  type = c("class", "raw", "rawprob"),
  sparse = FALSE,
  threshold = .Machine$double.eps,
  check = TRUE,
  ...
)

## S3 method for class 'fnb.gaussian'
predict(
  object,
  newdata,
  type = c("class", "raw", "rawprob"),
  sparse = FALSE,
  threshold = .Machine$double.eps,
  check = TRUE,
  ...
)

## S3 method for class 'fnb.multinomial'
predict(
  object,
  newdata,
  type = c("class", "raw", "rawprob"),
  sparse = FALSE,
  threshold = .Machine$double.eps,
  check = TRUE,
  ...
)

## S3 method for class 'fnb.poisson'
predict(
  object,
  newdata,
  type = c("class", "raw", "rawprob"),
  sparse = FALSE,
  threshold = .Machine$double.eps,
  check = TRUE,
  ...
)

## S3 method for class 'fastNaiveBayes'
predict(
  object,
  newdata,
  type = c("class", "raw"),
  sparse = FALSE,
  threshold = .Machine$double.eps,
  check = TRUE,
  ...
)
## S3 method for class 'fnb.bernoulli'
predict(
  object,
  newdata,
  type = c("class", "raw", "rawprob"),
  sparse = FALSE,
  threshold = .Machine$double.eps,
  check = TRUE,
  ...
)

## S3 method for class 'fnb.gaussian'
predict(
  object,
  newdata,
  type = c("class", "raw", "rawprob"),
  sparse = FALSE,
  threshold = .Machine$double.eps,
  check = TRUE,
  ...
)

## S3 method for class 'fnb.multinomial'
predict(
  object,
  newdata,
  type = c("class", "raw", "rawprob"),
  sparse = FALSE,
  threshold = .Machine$double.eps,
  check = TRUE,
  ...
)

## S3 method for class 'fnb.poisson'
predict(
  object,
  newdata,
  type = c("class", "raw", "rawprob"),
  sparse = FALSE,
  threshold = .Machine$double.eps,
  check = TRUE,
  ...
)

## S3 method for class 'fastNaiveBayes'
predict(
  object,
  newdata,
  type = c("class", "raw"),
  sparse = FALSE,
  threshold = .Machine$double.eps,
  check = TRUE,
  ...
)

Arguments

`object`	A fitted object of class "fnb.bernoulli", "fnb.gaussian", "fnb.multinomial" or "fastNaiveBayes".
`newdata`	A numeric matrix. A Sparse dgcMatrix is also accepted. Note: if fnb.naiveBayes or fnb.gaussian or fnb.train was used to create the model, then if newdata contains features that were not encountered in the training data, these are omitted from the prediction. Furthermore, newdata can contain fewer features than encountered in the training data. In this case, newdata will be padded with extra columns all filled with 0's.
`type`	If "raw", the conditional a-posterior probabilities for each class are returned, and the class with maximal probability else.
`sparse`	Use a sparse matrix? If true a sparse matrix will be constructed from x. It's possible to directly feed a sparse dgcMatrix as x, which will set this parameter to TRUE
`threshold`	A threshold for the minimum probability. For Bernoulli and Multinomial event models Laplace smoothing should solve this, but in the case of Gaussian event models, this ensures numerical probabilities.
`check`	Whether to perform formal checks on the input. Set to false, if this is not necessary and speed is of the essence
`...`	not used

Value

If type = 'class', a factor with classified class levels. If type = 'raw', a matrix with the predicted probabilities of each class, where each column in the matrix corresponds to a class level.

This data originally came from Crowdflower's Data for Everyone library.

Description

As the original source says,

Usage

tweets
tweets

Format

A data frame with 14640 rows and 2 columns

airline_sentiment: sentiment, as either 'negative','neutral','positive'
text: raw text, character

Details

"A sentiment analysis job about the problems of each major U.S. airline. Twitter data was scraped from February of 2015 and contributors were asked to first classify positive, negative, and neutral tweets, followed by categorizing negative reasons (such as "late flight" or "rude service")."

The data provided here is an altered version of the original source.

Source

https://www.figure-eight.com/data-for-everyone/

This data originally came from Crowdflower's Data for Everyone library.

Description

As the original source says,

Usage

tweetsDTM
tweetsDTM

Format

A data frame with 14640 rows and 2186 columns

airline_sentiment: sentiment, as either 'negative','neutral','positive'
said: Frequency count, numeric
virginamerica: Frequency count, numeric
commerci: Frequency count, numeric
experi: Frequency count, numeric
plus: Frequency count, numeric
anoth: Frequency count, numeric
mean: Frequency count, numeric
must: Frequency count, numeric
need: Frequency count, numeric
take: Frequency count, numeric
today: Frequency count, numeric
trip: Frequency count, numeric
amp: Frequency count, numeric
blast: Frequency count, numeric
entertain: Frequency count, numeric
face: Frequency count, numeric
guest: Frequency count, numeric
littl: Frequency count, numeric
realli: Frequency count, numeric
recours: Frequency count, numeric
bad: Frequency count, numeric
big: Frequency count, numeric
thing: Frequency count, numeric
fli: Frequency count, numeric
flight: Frequency count, numeric
pay: Frequency count, numeric
play: Frequency count, numeric
seat: Frequency count, numeric
serious: Frequency count, numeric
away: Frequency count, numeric
everi: Frequency count, numeric
near: Frequency count, numeric
time: Frequency count, numeric
wonut: Frequency count, numeric
yes: Frequency count, numeric
hat: Frequency count, numeric
miss: Frequency count, numeric
opportun: Frequency count, numeric
without: Frequency count, numeric
now: Frequency count, numeric
well: Frequency count, numeric
amaz: Frequency count, numeric
arriv: Frequency count, numeric
earli: Frequency count, numeric
good: Frequency count, numeric
hour: Frequency count, numeric
among: Frequency count, numeric
caus: Frequency count, numeric
death: Frequency count, numeric
know: Frequency count, numeric
lead: Frequency count, numeric
second: Frequency count, numeric
suicid: Frequency count, numeric
teen: Frequency count, numeric
better: Frequency count, numeric
much: Frequency count, numeric
pretti: Frequency count, numeric
alreadi: Frequency count, numeric
australia: Frequency count, numeric
deal: Frequency count, numeric
even: Frequency count, numeric
gone: Frequency count, numeric
great: Frequency count, numeric
think: Frequency count, numeric
yet: Frequency count, numeric
fabul: Frequency count, numeric
sky: Frequency count, numeric
stress: Frequency count, numeric
travel: Frequency count, numeric
thank: Frequency count, numeric
mia: Frequency count, numeric
schedul: Frequency count, numeric
still: Frequency count, numeric
america: Frequency count, numeric
countri: Frequency count, numeric
cross: Frequency count, numeric
excit: Frequency count, numeric
first: Frequency count, numeric
heard: Frequency count, numeric
lax: Frequency count, numeric
mco: Frequency count, numeric
noth: Frequency count, numeric
virgin: Frequency count, numeric
due: Frequency count, numeric
either: Frequency count, numeric
flew: Frequency count, numeric
fulli: Frequency count, numeric
help: Frequency count, numeric
larg: Frequency count, numeric
last: Frequency count, numeric
nyc: Frequency count, numeric
sfo: Frequency count, numeric
side: Frequency count, numeric
sit: Frequency count, numeric
two: Frequency count, numeric
week: Frequency count, numeric
cent: Frequency count, numeric
uuo: Frequency count, numeric
awesom: Frequency count, numeric
pleas: Frequency count, numeric
want: Frequency count, numeric
avail: Frequency count, numeric
carrier: Frequency count, numeric
fare: Frequency count, numeric
may: Frequency count, numeric
select: Frequency count, numeric
three: Frequency count, numeric
love: Frequency count, numeric
brand: Frequency count, numeric
feel: Frequency count, numeric
anytim: Frequency count, numeric
make: Frequency count, numeric
non: Frequency count, numeric
soon: Frequency count, numeric
stop: Frequency count, numeric
will: Frequency count, numeric
free: Frequency count, numeric
friend: Frequency count, numeric
gave: Frequency count, numeric
guy: Frequency count, numeric
internet: Frequency count, numeric
mess: Frequency count, numeric
reserv: Frequency count, numeric
appli: Frequency count, numeric
call: Frequency count, numeric
email: Frequency count, numeric
match: Frequency count, numeric
program: Frequency count, numeric
respons: Frequency count, numeric
status: Frequency count, numeric
abl: Frequency count, numeric
anyth: Frequency count, numeric
eat: Frequency count, numeric
fail: Frequency count, numeric
food: Frequency count, numeric
happen: Frequency count, numeric
hrs: Frequency count, numeric
least: Frequency count, numeric
next: Frequency count, numeric
option: Frequency count, numeric
say: Frequency count, numeric
site: Frequency count, numeric
togeth: Frequency count, numeric
worri: Frequency count, numeric
air: Frequency count, numeric
cold: Frequency count, numeric
get: Frequency count, numeric
ewr: Frequency count, numeric
eye: Frequency count, numeric
middl: Frequency count, numeric
red: Frequency count, numeric
add: Frequency count, numeric
birthday: Frequency count, numeric
book: Frequency count, numeric
cool: Frequency count, numeric
elev: Frequency count, numeric
enter: Frequency count, numeric
just: Frequency count, numeric
name: Frequency count, numeric
problem: Frequency count, numeric
club: Frequency count, numeric
current: Frequency count, numeric
onlin: Frequency count, numeric
oper: Frequency count, numeric
post: Frequency count, numeric
answer: Frequency count, numeric
expens: Frequency count, numeric
headphon: Frequency count, numeric
iad: Frequency count, numeric
left: Frequency count, numeric
number: Frequency count, numeric
one: Frequency count, numeric
await: Frequency count, numeric
phone: Frequency count, numeric
prefer: Frequency count, numeric
return: Frequency count, numeric
use: Frequency count, numeric
end: Frequency count, numeric
hawaii: Frequency count, numeric
news: Frequency count, numeric
start: Frequency count, numeric
via: Frequency count, numeric
year: Frequency count, numeric
nice: Frequency count, numeric
takeoff: Frequency count, numeric
touchdown: Frequency count, numeric
best: Frequency count, numeric
ever: Frequency count, numeric
way: Frequency count, numeric
airlin: Frequency count, numeric
around: Frequency count, numeric
done: Frequency count, numeric
hand: Frequency count, numeric
can: Frequency count, numeric
chat: Frequency count, numeric
support: Frequency count, numeric
work: Frequency count, numeric
angel: Frequency count, numeric
beyond: Frequency count, numeric
sign: Frequency count, numeric
view: Frequency count, numeric
account: Frequency count, numeric
flyer: Frequency count, numeric
hard: Frequency count, numeric
hey: Frequency count, numeric
plz: Frequency count, numeric
upgrad: Frequency count, numeric
win: Frequency count, numeric
citi: Frequency count, numeric
expir: Frequency count, numeric
move: Frequency count, numeric
new: Frequency count, numeric
ticket: Frequency count, numeric
unus: Frequency count, numeric
dalla: Frequency count, numeric
feb: Frequency count, numeric
leav: Frequency count, numeric
seattl: Frequency count, numeric
reason: Frequency count, numeric
rock: Frequency count, numeric
dream: Frequency count, numeric
mind: Frequency count, numeric
wow: Frequency count, numeric
agre: Frequency count, numeric
carrieunderwood: Frequency count, numeric
ladygaga: Frequency count, numeric
night: Frequency count, numeric
oscar: Frequency count, numeric
ago: Frequency count, numeric
minut: Frequency count, numeric
show: Frequency count, numeric
suppos: Frequency count, numeric
websit: Frequency count, numeric
andrew: Frequency count, numeric
impress: Frequency count, numeric
juli: Frequency count, numeric
though: Frequency count, numeric
atlanta: Frequency count, numeric
wish: Frequency count, numeric
februari: Frequency count, numeric
load: Frequency count, numeric
never: Frequency count, numeric
page: Frequency count, numeric
sinc: Frequency count, numeric
thx: Frequency count, numeric
tri: Frequency count, numeric
stat: Frequency count, numeric
ladi: Frequency count, numeric
carri: Frequency count, numeric
let: Frequency count, numeric
market: Frequency count, numeric
song: Frequency count, numeric
shown: Frequency count, numeric
mari: Frequency count, numeric
sorri: Frequency count, numeric
beat: Frequency count, numeric
check: Frequency count, numeric
dal: Frequency count, numeric
dca: Frequency count, numeric
someon: Frequency count, numeric
earlier: Frequency count, numeric
hold: Frequency count, numeric
tonight: Frequency count, numeric
award: Frequency count, numeric
congrat: Frequency count, numeric
bag: Frequency count, numeric
everyth: Frequency count, numeric
fine: Frequency count, numeric
lost: Frequency count, numeric
card: Frequency count, numeric
chang: Frequency count, numeric
credit: Frequency count, numeric
fee: Frequency count, numeric
waiv: Frequency count, numeric
custom: Frequency count, numeric
servic: Frequency count, numeric
team: Frequency count, numeric
track: Frequency count, numeric
baggag: Frequency count, numeric
dirti: Frequency count, numeric
floor: Frequency count, numeric
game: Frequency count, numeric
step: Frequency count, numeric
tabl: Frequency count, numeric
crew: Frequency count, numeric
like: Frequency count, numeric
plane: Frequency count, numeric
ride: Frequency count, numeric
bill: Frequency count, numeric
correct: Frequency count, numeric
morn: Frequency count, numeric
sat: Frequency count, numeric
yall: Frequency count, numeric
feet: Frequency count, numeric
film: Frequency count, numeric
student: Frequency count, numeric
watch: Frequency count, numeric
differ: Frequency count, numeric
media: Frequency count, numeric
anyway: Frequency count, numeric
asap: Frequency count, numeric
human: Frequency count, numeric
speak: Frequency count, numeric
biz: Frequency count, numeric
jetblu: Frequency count, numeric
southwestair: Frequency count, numeric
inflight: Frequency count, numeric
interest: Frequency count, numeric
member: Frequency count, numeric
delay: Frequency count, numeric
late: Frequency count, numeric
whenev: Frequency count, numeric
cancel: Frequency count, numeric
four: Frequency count, numeric
busi: Frequency count, numeric
disappoint: Frequency count, numeric
meet: Frequency count, numeric
share: Frequency count, numeric
ium: Frequency count, numeric
troubl: Frequency count, numeric
wife: Frequency count, numeric
bring: Frequency count, numeric
code: Frequency count, numeric
bet: Frequency count, numeric
random: Frequency count, numeric
home: Frequency count, numeric
life: Frequency count, numeric
back: Frequency count, numeric
yeah: Frequency count, numeric
point: Frequency count, numeric
recent: Frequency count, numeric
flightl: Frequency count, numeric
jfk: Frequency count, numeric
saturday: Frequency count, numeric
video: Frequency count, numeric
went: Frequency count, numeric
land: Frequency count, numeric
redirect: Frequency count, numeric
btw: Frequency count, numeric
user: Frequency count, numeric
desktop: Frequency count, numeric
mobil: Frequency count, numeric
bin: Frequency count, numeric
class: Frequency count, numeric
passeng: Frequency count, numeric
remov: Frequency count, numeric
scan: Frequency count, numeric
told: Frequency count, numeric
uncomfort: Frequency count, numeric
find: Frequency count, numeric
anyon: Frequency count, numeric
useless: Frequency count, numeric
boy: Frequency count, numeric
thursday: Frequency count, numeric
appoint: Frequency count, numeric
music: Frequency count, numeric
bought: Frequency count, numeric
direct: Frequency count, numeric
fuel: Frequency count, numeric
layov: Frequency count, numeric
unexpect: Frequency count, numeric
vega: Frequency count, numeric
exp: Frequency count, numeric
peopl: Frequency count, numeric
customerservic: Frequency count, numeric
uouo: Frequency count, numeric
hung: Frequency count, numeric
line: Frequency count, numeric
sarcasm: Frequency count, numeric
info: Frequency count, numeric
plain: Frequency count, numeric
text: Frequency count, numeric
version: Frequency count, numeric
look: Frequency count, numeric
weather: Frequency count, numeric
getaway: Frequency count, numeric
lot: Frequency count, numeric
oneway: Frequency count, numeric
uiio: Frequency count, numeric
come: Frequency count, numeric
horribl: Frequency count, numeric
phl: Frequency count, numeric
concern: Frequency count, numeric
tech: Frequency count, numeric
comfort: Frequency count, numeric
easi: Frequency count, numeric
flown: Frequency count, numeric
repres: Frequency count, numeric
beauti: Frequency count, numeric
kick: Frequency count, numeric
rep: Frequency count, numeric
design: Frequency count, numeric
right: Frequency count, numeric
secur: Frequency count, numeric
gate: Frequency count, numeric
kept: Frequency count, numeric
las: Frequency count, numeric
run: Frequency count, numeric
wait: Frequency count, numeric
browser: Frequency count, numeric
folk: Frequency count, numeric
total: Frequency count, numeric
connect: Frequency count, numeric
long: Frequency count, numeric
min: Frequency count, numeric
seem: Frequency count, numeric
francisco: Frequency count, numeric
outstand: Frequency count, numeric
san: Frequency count, numeric
absolut: Frequency count, numeric
delight: Frequency count, numeric
complimentari: Frequency count, numeric
provid: Frequency count, numeric
intern: Frequency count, numeric
that: Frequency count, numeric
complet: Frequency count, numeric
depart: Frequency count, numeric
month: Frequency count, numeric
nonstop: Frequency count, numeric
link: Frequency count, numeric
precheck: Frequency count, numeric
process: Frequency count, numeric
tsa: Frequency count, numeric
hotel: Frequency count, numeric
terribl: Frequency count, numeric
cabo: Frequency count, numeric
assist: Frequency count, numeric
give: Frequency count, numeric
shame: Frequency count, numeric
yesterday: Frequency count, numeric
advis: Frequency count, numeric
dog: Frequency count, numeric
dull: Frequency count, numeric
longer: Frequency count, numeric
pls: Frequency count, numeric
queue: Frequency count, numeric
regist: Frequency count, numeric
redcarpet: Frequency count, numeric
drop: Frequency count, numeric
alway: Frequency count, numeric
buy: Frequency count, numeric
creat: Frequency count, numeric
frustrat: Frequency count, numeric
afford: Frequency count, numeric
buck: Frequency count, numeric
extra: Frequency count, numeric
hire: Frequency count, numeric
lame: Frequency count, numeric
luggag: Frequency count, numeric
might: Frequency count, numeric
cake: Frequency count, numeric
world: Frequency count, numeric
flt: Frequency count, numeric
midnight: Frequency count, numeric
monday: Frequency count, numeric
sooner: Frequency count, numeric
cant: Frequency count, numeric
imagin: Frequency count, numeric
indic: Frequency count, numeric
web: Frequency count, numeric
ran: Frequency count, numeric
staff: Frequency count, numeric
super: Frequency count, numeric
across: Frequency count, numeric
offer: Frequency count, numeric
paid: Frequency count, numeric
premium: Frequency count, numeric
sad: Frequency count, numeric
infant: Frequency count, numeric
possibl: Frequency count, numeric
question: Frequency count, numeric
welcom: Frequency count, numeric
refresh: Frequency count, numeric
damag: Frequency count, numeric
polici: Frequency count, numeric
understand: Frequency count, numeric
destroy: Frequency count, numeric
alon: Frequency count, numeric
board: Frequency count, numeric
kid: Frequency count, numeric
prioriti: Frequency count, numeric
special: Frequency count, numeric
happi: Frequency count, numeric
purchas: Frequency count, numeric
definit: Frequency count, numeric
field: Frequency count, numeric
dfw: Frequency count, numeric
lga: Frequency count, numeric
driver: Frequency count, numeric
friday: Frequency count, numeric
licens: Frequency count, numeric
contact: Frequency count, numeric
error: Frequency count, numeric
keep: Frequency count, numeric
button: Frequency count, numeric
reschedul: Frequency count, numeric
fix: Frequency count, numeric
rang: Frequency count, numeric
got: Frequency count, numeric
tomorrow: Frequency count, numeric
unaccept: Frequency count, numeric
stuck: Frequency count, numeric
includ: Frequency count, numeric
pair: Frequency count, numeric
white: Frequency count, numeric
wine: Frequency count, numeric
agent: Frequency count, numeric
close: Frequency count, numeric
dullesairport: Frequency count, numeric
silver: Frequency count, numeric
austin: Frequency count, numeric
plan: Frequency count, numeric
rout: Frequency count, numeric
central: Frequency count, numeric
normal: Frequency count, numeric
receiv: Frequency count, numeric
repli: Frequency count, numeric
smh: Frequency count, numeric
airport: Frequency count, numeric
checkin: Frequency count, numeric
desk: Frequency count, numeric
logan: Frequency count, numeric
open: Frequency count, numeric
jump: Frequency count, numeric
daili: Frequency count, numeric
luv: Frequency count, numeric
april: Frequency count, numeric
begin: Frequency count, numeric
fuck: Frequency count, numeric
unit: Frequency count, numeric
follow: Frequency count, numeric
apolog: Frequency count, numeric
mani: Frequency count, numeric
respond: Frequency count, numeric
wors: Frequency count, numeric
money: Frequency count, numeric
reimburs: Frequency count, numeric
spend: Frequency count, numeric
strand: Frequency count, numeric
choic: Frequency count, numeric
sjc: Frequency count, numeric
southwest: Frequency count, numeric
claim: Frequency count, numeric
confirm: Frequency count, numeric
day: Frequency count, numeric
inquir: Frequency count, numeric
bos: Frequency count, numeric
notif: Frequency count, numeric
rebook: Frequency count, numeric
met: Frequency count, numeric
gold: Frequency count, numeric
cmh: Frequency count, numeric
see: Frequency count, numeric
worst: Frequency count, numeric
stuff: Frequency count, numeric
wrong: Frequency count, numeric
head: Frequency count, numeric
issu: Frequency count, numeric
item: Frequency count, numeric
americanairlin: Frequency count, numeric
lose: Frequency count, numeric
suck: Frequency count, numeric
dmd: Frequency count, numeric
drive: Frequency count, numeric
flightlat: Frequency count, numeric
mon: Frequency count, numeric
notic: Frequency count, numeric
boston: Frequency count, numeric
abil: Frequency count, numeric
expect: Frequency count, numeric
stink: Frequency count, numeric
danc: Frequency count, numeric
high: Frequency count, numeric
school: Frequency count, numeric
appar: Frequency count, numeric
faster: Frequency count, numeric
quick: Frequency count, numeric
nervous: Frequency count, numeric
sent: Frequency count, numeric
pictur: Frequency count, numeric
wing: Frequency count, numeric
crisi: Frequency count, numeric
pressur: Frequency count, numeric
texa: Frequency count, numeric
job: Frequency count, numeric
pilot: Frequency count, numeric
snow: Frequency count, numeric
afternoon: Frequency count, numeric
area: Frequency count, numeric
york: Frequency count, numeric
mention: Frequency count, numeric
reclin: Frequency count, numeric
row: Frequency count, numeric
drink: Frequency count, numeric
handl: Frequency count, numeric
mechan: Frequency count, numeric
scare: Frequency count, numeric
kill: Frequency count, numeric
twitter: Frequency count, numeric
charg: Frequency count, numeric
refund: Frequency count, numeric
refus: Frequency count, numeric
access: Frequency count, numeric
canut: Frequency count, numeric
ipad: Frequency count, numeric
iphon: Frequency count, numeric
passbook: Frequency count, numeric
click: Frequency count, numeric
broken: Frequency count, numeric
forward: Frequency count, numeric
sec: Frequency count, numeric
cost: Frequency count, numeric
ugh: Frequency count, numeric
along: Frequency count, numeric
pdx: Frequency count, numeric
put: Frequency count, numeric
gonna: Frequency count, numeric
bug: Frequency count, numeric
itus: Frequency count, numeric
report: Frequency count, numeric
bit: Frequency count, numeric
center: Frequency count, numeric
attend: Frequency count, numeric
password: Frequency count, numeric
reset: Frequency count, numeric
base: Frequency count, numeric
disrupt: Frequency count, numeric
someth: Frequency count, numeric
departur: Frequency count, numeric
palm: Frequency count, numeric
spring: Frequency count, numeric
fun: Frequency count, numeric
sound: Frequency count, numeric
updat: Frequency count, numeric
count: Frequency count, numeric
somehow: Frequency count, numeric
continu: Frequency count, numeric
sort: Frequency count, numeric
sweet: Frequency count, numeric
coffe: Frequency count, numeric
ice: Frequency count, numeric
assault: Frequency count, numeric
file: Frequency count, numeric
trust: Frequency count, numeric
destin: Frequency count, numeric
sever: Frequency count, numeric
wheel: Frequency count, numeric
itinerari: Frequency count, numeric
abq: Frequency count, numeric
becom: Frequency count, numeric
event: Frequency count, numeric
girl: Frequency count, numeric
inspir: Frequency count, numeric
march: Frequency count, numeric
entir: Frequency count, numeric
improv: Frequency count, numeric
request: Frequency count, numeric
treat: Frequency count, numeric
window: Frequency count, numeric
grand: Frequency count, numeric
exhaust: Frequency count, numeric
flier: Frequency count, numeric
frequent: Frequency count, numeric
inconveni: Frequency count, numeric
purpos: Frequency count, numeric
wtf: Frequency count, numeric
full: Frequency count, numeric
boo: Frequency count, numeric
place: Frequency count, numeric
result: Frequency count, numeric
usa: Frequency count, numeric
instead: Frequency count, numeric
pillow: Frequency count, numeric
race: Frequency count, numeric
advantag: Frequency count, numeric
fight: Frequency count, numeric
salt: Frequency count, numeric
behind: Frequency count, numeric
cabin: Frequency count, numeric
fav: Frequency count, numeric
hot: Frequency count, numeric
pari: Frequency count, numeric
uio: Frequency count, numeric
surgeri: Frequency count, numeric
tell: Frequency count, numeric
suitcas: Frequency count, numeric
past: Frequency count, numeric
order: Frequency count, numeric
regul: Frequency count, numeric
atlant: Frequency count, numeric
benefit: Frequency count, numeric
virginatlant: Frequency count, numeric
came: Frequency count, numeric
husband: Frequency count, numeric
screen: Frequency count, numeric
bare: Frequency count, numeric
light: Frequency count, numeric
turbul: Frequency count, numeric
profit: Frequency count, numeric
funni: Frequency count, numeric
stori: Frequency count, numeric
forecast: Frequency count, numeric
nytim: Frequency count, numeric
applic: Frequency count, numeric
flylaxairport: Frequency count, numeric
posit: Frequency count, numeric
wonder: Frequency count, numeric
despit: Frequency count, numeric
revenu: Frequency count, numeric
competit: Frequency count, numeric
increas: Frequency count, numeric
sos: Frequency count, numeric
degre: Frequency count, numeric
wind: Frequency count, numeric
safeti: Frequency count, numeric
wanna: Frequency count, numeric
hope: Frequency count, numeric
newark: Frequency count, numeric
inappropri: Frequency count, numeric
probabl: Frequency count, numeric
save: Frequency count, numeric
standbi: Frequency count, numeric
comp: Frequency count, numeric
brought: Frequency count, numeric
readi: Frequency count, numeric
manag: Frequency count, numeric
battl: Frequency count, numeric
old: Frequency count, numeric
treatment: Frequency count, numeric
uou: Frequency count, numeric
urgent: Frequency count, numeric
half: Frequency count, numeric
less: Frequency count, numeric
price: Frequency count, numeric
round: Frequency count, numeric
stun: Frequency count, numeric
dtw: Frequency count, numeric
sold: Frequency count, numeric
promo: Frequency count, numeric
made: Frequency count, numeric
paperwork: Frequency count, numeric
promis: Frequency count, numeric
resolut: Frequency count, numeric
perform: Frequency count, numeric
care: Frequency count, numeric
challeng: Frequency count, numeric
mileag: Frequency count, numeric
ball: Frequency count, numeric
americanair: Frequency count, numeric
gma: Frequency count, numeric
glad: Frequency count, numeric
took: Frequency count, numeric
earn: Frequency count, numeric
cheer: Frequency count, numeric
coupl: Frequency count, numeric
messag: Frequency count, numeric
easili: Frequency count, numeric
smooth: Frequency count, numeric
empti: Frequency count, numeric
forc: Frequency count, numeric
small: Frequency count, numeric
space: Frequency count, numeric
slow: Frequency count, numeric
loyal: Frequency count, numeric
solut: Frequency count, numeric
spoke: Frequency count, numeric
jacket: Frequency count, numeric
convers: Frequency count, numeric
method: Frequency count, numeric
partner: Frequency count, numeric
payment: Frequency count, numeric
rate: Frequency count, numeric
visa: Frequency count, numeric
promot: Frequency count, numeric
recommend: Frequency count, numeric
aus: Frequency count, numeric
turn: Frequency count, numeric
cours: Frequency count, numeric
famili: Frequency count, numeric
receipt: Frequency count, numeric
badg: Frequency count, numeric
superior: Frequency count, numeric
standard: Frequency count, numeric
pick: Frequency count, numeric
tweet: Frequency count, numeric
car: Frequency count, numeric
rental: Frequency count, numeric
child: Frequency count, numeric
cust: Frequency count, numeric
lap: Frequency count, numeric
chanc: Frequency count, numeric
gift: Frequency count, numeric
bank: Frequency count, numeric
constant: Frequency count, numeric
joke: Frequency count, numeric
also: Frequency count, numeric
bday: Frequency count, numeric
eastern: Frequency count, numeric
ella: Frequency count, numeric
grandma: Frequency count, numeric
greet: Frequency count, numeric
stewardess: Frequency count, numeric
tix: Frequency count, numeric
transact: Frequency count, numeric
moment: Frequency count, numeric
send: Frequency count, numeric
havenut: Frequency count, numeric
submit: Frequency count, numeric
fat: Frequency count, numeric
ceo: Frequency count, numeric
low: Frequency count, numeric
model: Frequency count, numeric
brilliant: Frequency count, numeric
omg: Frequency count, numeric
thought: Frequency count, numeric
comput: Frequency count, numeric
pull: Frequency count, numeric
incid: Frequency count, numeric
laptop: Frequency count, numeric
guess: Frequency count, numeric
road: Frequency count, numeric
announc: Frequency count, numeric
dollar: Frequency count, numeric
deserv: Frequency count, numeric
address: Frequency count, numeric
bounc: Frequency count, numeric
exist: Frequency count, numeric
fyi: Frequency count, numeric
requir: Frequency count, numeric
svc: Frequency count, numeric
toward: Frequency count, numeric
app: Frequency count, numeric
develop: Frequency count, numeric
favorit: Frequency count, numeric
channel: Frequency count, numeric
crap: Frequency count, numeric
set: Frequency count, numeric
integr: Frequency count, numeric
mexico: Frequency count, numeric
paper: Frequency count, numeric
wast: Frequency count, numeric
accept: Frequency count, numeric
system: Frequency count, numeric
black: Frequency count, numeric
tea: Frequency count, numeric
spread: Frequency count, numeric
learn: Frequency count, numeric
experienc: Frequency count, numeric
incred: Frequency count, numeric
philadelphia: Frequency count, numeric
houston: Frequency count, numeric
final: Frequency count, numeric
avgeek: Frequency count, numeric
forget: Frequency count, numeric
futur: Frequency count, numeric
jack: Frequency count, numeric
kinda: Frequency count, numeric
diego: Frequency count, numeric
malfunct: Frequency count, numeric
poor: Frequency count, numeric
thankyou: Frequency count, numeric
jose: Frequency count, numeric
compet: Frequency count, numeric
excel: Frequency count, numeric
portland: Frequency count, numeric
addit: Frequency count, numeric
thur: Frequency count, numeric
uau: Frequency count, numeric
carryon: Frequency count, numeric
lock: Frequency count, numeric
group: Frequency count, numeric
room: Frequency count, numeric
nightmar: Frequency count, numeric
classi: Frequency count, numeric
strong: Frequency count, numeric
sure: Frequency count, numeric
shit: Frequency count, numeric
bump: Frequency count, numeric
luckili: Frequency count, numeric
rough: Frequency count, numeric
perfect: Frequency count, numeric
rais: Frequency count, numeric
stay: Frequency count, numeric
sun: Frequency count, numeric
man: Frequency count, numeric
wifi: Frequency count, numeric
donut: Frequency count, numeric
iull: Frequency count, numeric
saw: Frequency count, numeric
dad: Frequency count, numeric
part: Frequency count, numeric
whole: Frequency count, numeric
europ: Frequency count, numeric
short: Frequency count, numeric
abc: Frequency count, numeric
overhead: Frequency count, numeric
person: Frequency count, numeric
ask: Frequency count, numeric
luck: Frequency count, numeric
accommod: Frequency count, numeric
dear: Frequency count, numeric
lol: Frequency count, numeric
actual: Frequency count, numeric
other: Frequency count, numeric
serv: Frequency count, numeric
affect: Frequency count, numeric
shock: Frequency count, numeric
storm: Frequency count, numeric
umm: Frequency count, numeric
advanc: Frequency count, numeric
cut: Frequency count, numeric
philli: Frequency count, numeric
main: Frequency count, numeric
penalti: Frequency count, numeric
industri: Frequency count, numeric
bonus: Frequency count, numeric
regard: Frequency count, numeric
movi: Frequency count, numeric
resolv: Frequency count, numeric
word: Frequency count, numeric
deic: Frequency count, numeric
lack: Frequency count, numeric
common: Frequency count, numeric
fill: Frequency count, numeric
express: Frequency count, numeric
hop: Frequency count, numeric
huge: Frequency count, numeric
popular: Frequency count, numeric
orlando: Frequency count, numeric
accid: Frequency count, numeric
tough: Frequency count, numeric
altern: Frequency count, numeric
hook: Frequency count, numeric
prevent: Frequency count, numeric
domest: Frequency count, numeric
law: Frequency count, numeric
auto: Frequency count, numeric
economi: Frequency count, numeric
logic: Frequency count, numeric
transfer: Frequency count, numeric
shoe: Frequency count, numeric
case: Frequency count, numeric
david: Frequency count, numeric
cousin: Frequency count, numeric
januari: Frequency count, numeric
voucher: Frequency count, numeric
mail: Frequency count, numeric
compani: Frequency count, numeric
execut: Frequency count, numeric
manner: Frequency count, numeric
mayb: Frequency count, numeric
chase: Frequency count, numeric
pass: Frequency count, numeric
son: Frequency count, numeric
weak: Frequency count, numeric
didnt: Frequency count, numeric
given: Frequency count, numeric
jan: Frequency count, numeric
miami: Frequency count, numeric
septemb: Frequency count, numeric
explain: Frequency count, numeric
talk: Frequency count, numeric
almost: Frequency count, numeric
daughter: Frequency count, numeric
ppl: Frequency count, numeric
flightr: Frequency count, numeric
repeat: Frequency count, numeric
anymor: Frequency count, numeric
platinum: Frequency count, numeric
termin: Frequency count, numeric
badcustomerservic: Frequency count, numeric
instruct: Frequency count, numeric
rude: Frequency count, numeric
overnight: Frequency count, numeric
client: Frequency count, numeric
iah: Frequency count, numeric
taken: Frequency count, numeric
accord: Frequency count, numeric
illeg: Frequency count, numeric
detail: Frequency count, numeric
dmed: Frequency count, numeric
charlott: Frequency count, numeric
ignor: Frequency count, numeric
touch: Frequency count, numeric
form: Frequency count, numeric
anywher: Frequency count, numeric
upon: Frequency count, numeric
ground: Frequency count, numeric
cessna: Frequency count, numeric
els: Frequency count, numeric
appreci: Frequency count, numeric
tarmac: Frequency count, numeric
outsid: Frequency count, numeric
break: Frequency count, numeric
guitar: Frequency count, numeric
truli: Frequency count, numeric
besid: Frequency count, numeric
third: Frequency count, numeric
disabl: Frequency count, numeric
search: Frequency count, numeric
enough: Frequency count, numeric
rule: Frequency count, numeric
denver: Frequency count, numeric
mistak: Frequency count, numeric
train: Frequency count, numeric
ord: Frequency count, numeric
avoid: Frequency count, numeric
found: Frequency count, numeric
supervisor: Frequency count, numeric
pre: Frequency count, numeric
preboard: Frequency count, numeric
dept: Frequency count, numeric
okc: Frequency count, numeric
thru: Frequency count, numeric
employe: Frequency count, numeric
equip: Frequency count, numeric
medic: Frequency count, numeric
upset: Frequency count, numeric
consider: Frequency count, numeric
intl: Frequency count, numeric
thnx: Frequency count, numeric
activ: Frequency count, numeric
emerg: Frequency count, numeric
militari: Frequency count, numeric
mom: Frequency count, numeric
wont: Frequency count, numeric
mile: Frequency count, numeric
mileageplus: Frequency count, numeric
complain: Frequency count, numeric
throw: Frequency count, numeric
unfortun: Frequency count, numeric
american: Frequency count, numeric
ahead: Frequency count, numeric
bird: Frequency count, numeric
coach: Frequency count, numeric
control: Frequency count, numeric
rather: Frequency count, numeric
sincer: Frequency count, numeric
bother: Frequency count, numeric
delta: Frequency count, numeric
unhelp: Frequency count, numeric
attempt: Frequency count, numeric
buddi: Frequency count, numeric
neglig: Frequency count, numeric
believ: Frequency count, numeric
fll: Frequency count, numeric
disappear: Frequency count, numeric
stand: Frequency count, numeric
record: Frequency count, numeric
nut: Frequency count, numeric
guid: Frequency count, numeric
read: Frequency count, numeric
bogota: Frequency count, numeric
everyon: Frequency count, numeric
inform: Frequency count, numeric
outbound: Frequency count, numeric
aircraft: Frequency count, numeric
switch: Frequency count, numeric
crash: Frequency count, numeric
knew: Frequency count, numeric
negoti: Frequency count, numeric
winter: Frequency count, numeric
coat: Frequency count, numeric
scam: Frequency count, numeric
reach: Frequency count, numeric
elsewher: Frequency count, numeric
honor: Frequency count, numeric
hear: Frequency count, numeric
quit: Frequency count, numeric
pathet: Frequency count, numeric
boot: Frequency count, numeric
unavail: Frequency count, numeric
minor: Frequency count, numeric
babi: Frequency count, numeric
mine: Frequency count, numeric
huh: Frequency count, numeric
goe: Frequency count, numeric
obvious: Frequency count, numeric
simpl: Frequency count, numeric
disrespect: Frequency count, numeric
neglect: Frequency count, numeric
enjoy: Frequency count, numeric
finger: Frequency count, numeric
zone: Frequency count, numeric
date: Frequency count, numeric
excus: Frequency count, numeric
zero: Frequency count, numeric
decemb: Frequency count, numeric
octob: Frequency count, numeric
sna: Frequency count, numeric
weekend: Frequency count, numeric
flightd: Frequency count, numeric
local: Frequency count, numeric
faith: Frequency count, numeric
ski: Frequency count, numeric
held: Frequency count, numeric
coast: Frequency count, numeric
tourist: Frequency count, numeric
listen: Frequency count, numeric
whoever: Frequency count, numeric
charact: Frequency count, numeric
limit: Frequency count, numeric
appear: Frequency count, numeric
doesnt: Frequency count, numeric
pop: Frequency count, numeric
coupon: Frequency count, numeric
ridicul: Frequency count, numeric
airfar: Frequency count, numeric
cheaper: Frequency count, numeric
heathrow: Frequency count, numeric
properti: Frequency count, numeric
complaint: Frequency count, numeric
ref: Frequency count, numeric
unhappi: Frequency count, numeric
jet: Frequency count, numeric
privat: Frequency count, numeric
fund: Frequency count, numeric
atl: Frequency count, numeric
matter: Frequency count, numeric
yep: Frequency count, numeric
loui: Frequency count, numeric
difficult: Frequency count, numeric
prepar: Frequency count, numeric
confid: Frequency count, numeric
seek: Frequency count, numeric
bot: Frequency count, numeric
worth: Frequency count, numeric
california: Frequency count, numeric
conf: Frequency count, numeric
communic: Frequency count, numeric
far: Frequency count, numeric
horrid: Frequency count, numeric
note: Frequency count, numeric
top: Frequency count, numeric
unitedairlin: Frequency count, numeric
kudo: Frequency count, numeric
usual: Frequency count, numeric
advisori: Frequency count, numeric
quot: Frequency count, numeric
heat: Frequency count, numeric
rememb: Frequency count, numeric
captain: Frequency count, numeric
extrem: Frequency count, numeric
effici: Frequency count, numeric
real: Frequency count, numeric
henc: Frequency count, numeric
cloth: Frequency count, numeric
curious: Frequency count, numeric
conveni: Frequency count, numeric
washington: Frequency count, numeric
chicago: Frequency count, numeric
china: Frequency count, numeric
leg: Frequency count, numeric
loung: Frequency count, numeric
dms: Frequency count, numeric
owe: Frequency count, numeric
okay: Frequency count, numeric
dead: Frequency count, numeric
proper: Frequency count, numeric
forgot: Frequency count, numeric
onto: Frequency count, numeric
atroci: Frequency count, numeric
imposs: Frequency count, numeric
esp: Frequency count, numeric
lhr: Frequency count, numeric
doubt: Frequency count, numeric
vacat: Frequency count, numeric
compliment: Frequency count, numeric
assur: Frequency count, numeric
nope: Frequency count, numeric
sleep: Frequency count, numeric
compens: Frequency count, numeric
origin: Frequency count, numeric
ruin: Frequency count, numeric
defin: Frequency count, numeric
inbound: Frequency count, numeric
valid: Frequency count, numeric
deliv: Frequency count, numeric
deliveri: Frequency count, numeric
hostag: Frequency count, numeric
lbs: Frequency count, numeric
machin: Frequency count, numeric
write: Frequency count, numeric
blame: Frequency count, numeric
previous: Frequency count, numeric
tel: Frequency count, numeric
aviv: Frequency count, numeric
uiunit: Frequency count, numeric
feedback: Frequency count, numeric
taxi: Frequency count, numeric
action: Frequency count, numeric
solv: Frequency count, numeric
tire: Frequency count, numeric
comment: Frequency count, numeric
clt: Frequency count, numeric
idea: Frequency count, numeric
neveragain: Frequency count, numeric
within: Frequency count, numeric
cancun: Frequency count, numeric
continent: Frequency count, numeric
equal: Frequency count, numeric
deep: Frequency count, numeric
figur: Frequency count, numeric
fran: Frequency count, numeric
pack: Frequency count, numeric
pax: Frequency count, numeric
screw: Frequency count, numeric
hou: Frequency count, numeric
pos: Frequency count, numeric
wake: Frequency count, numeric
counter: Frequency count, numeric
nobodi: Frequency count, numeric
flyohar: Frequency count, numeric
regret: Frequency count, numeric
annoy: Frequency count, numeric
door: Frequency count, numeric
premier: Frequency count, numeric
bullshit: Frequency count, numeric
phoenix: Frequency count, numeric
yea: Frequency count, numeric
encount: Frequency count, numeric
stellar: Frequency count, numeric
front: Frequency count, numeric
pocket: Frequency count, numeric
rip: Frequency count, numeric
absurd: Frequency count, numeric
fact: Frequency count, numeric
walk: Frequency count, numeric
happili: Frequency count, numeric
public: Frequency count, numeric
stranger: Frequency count, numeric
nah: Frequency count, numeric
split: Frequency count, numeric
wks: Frequency count, numeric
bwi: Frequency count, numeric
appropri: Frequency count, numeric
review: Frequency count, numeric
overbook: Frequency count, numeric
unprofession: Frequency count, numeric
consid: Frequency count, numeric
corp: Frequency count, numeric
unabl: Frequency count, numeric
flightat: Frequency count, numeric
courtesi: Frequency count, numeric
diff: Frequency count, numeric
tag: Frequency count, numeric
certif: Frequency count, numeric
bar: Frequency count, numeric
appl: Frequency count, numeric
bunch: Frequency count, numeric
adopt: Frequency count, numeric
outlet: Frequency count, numeric
incompet: Frequency count, numeric
finish: Frequency count, numeric
exact: Frequency count, numeric
carousel: Frequency count, numeric
easier: Frequency count, numeric
monitor: Frequency count, numeric
friendlyski: Frequency count, numeric
spare: Frequency count, numeric
unless: Frequency count, numeric
disast: Frequency count, numeric
period: Frequency count, numeric
apart: Frequency count, numeric
fall: Frequency count, numeric
fleet: Frequency count, numeric
notcool: Frequency count, numeric
balanc: Frequency count, numeric
impact: Frequency count, numeric
major: Frequency count, numeric
refuel: Frequency count, numeric
hundr: Frequency count, numeric
quiet: Frequency count, numeric
rectifi: Frequency count, numeric
situat: Frequency count, numeric
spent: Frequency count, numeric
clue: Frequency count, numeric
liter: Frequency count, numeric
list: Frequency count, numeric
dia: Frequency count, numeric
remind: Frequency count, numeric
devic: Frequency count, numeric
insid: Frequency count, numeric
failur: Frequency count, numeric
assum: Frequency count, numeric
effort: Frequency count, numeric
finest: Frequency count, numeric
confus: Frequency count, numeric
airplan: Frequency count, numeric
project: Frequency count, numeric
softwar: Frequency count, numeric
ogg: Frequency count, numeric
display: Frequency count, numeric
howev: Frequency count, numeric
closest: Frequency count, numeric
clear: Frequency count, numeric
refer: Frequency count, numeric
discuss: Frequency count, numeric
shot: Frequency count, numeric
pacif: Frequency count, numeric
spot: Frequency count, numeric
generic: Frequency count, numeric
unnecessari: Frequency count, numeric
carseat: Frequency count, numeric
decis: Frequency count, numeric
kpu: Frequency count, numeric
kit: Frequency count, numeric
pjs: Frequency count, numeric
ensur: Frequency count, numeric
flat: Frequency count, numeric
lie: Frequency count, numeric
stl: Frequency count, numeric
membership: Frequency count, numeric
catch: Frequency count, numeric
karen: Frequency count, numeric
chicken: Frequency count, numeric
fair: Frequency count, numeric
den: Frequency count, numeric
ohar: Frequency count, numeric
reinstat: Frequency count, numeric
offic: Frequency count, numeric
attach: Frequency count, numeric
photo: Frequency count, numeric
damn: Frequency count, numeric
canada: Frequency count, numeric
yvr: Frequency count, numeric
divert: Frequency count, numeric
msi: Frequency count, numeric
canadian: Frequency count, numeric
male: Frequency count, numeric
pic: Frequency count, numeric
threaten: Frequency count, numeric
yell: Frequency count, numeric
tho: Frequency count, numeric
frm: Frequency count, numeric
reflight: Frequency count, numeric
sea: Frequency count, numeric
connector: Frequency count, numeric
gross: Frequency count, numeric
exampl: Frequency count, numeric
statement: Frequency count, numeric
otherwis: Frequency count, numeric
stood: Frequency count, numeric
inadequ: Frequency count, numeric
unfriendlyski: Frequency count, numeric
seen: Frequency count, numeric
singl: Frequency count, numeric
locat: Frequency count, numeric
boyfriend: Frequency count, numeric
gotta: Frequency count, numeric
stolen: Frequency count, numeric
wallet: Frequency count, numeric
til: Frequency count, numeric
repair: Frequency count, numeric
tuesday: Frequency count, numeric
fit: Frequency count, numeric
nonsens: Frequency count, numeric
incur: Frequency count, numeric
abt: Frequency count, numeric
deni: Frequency count, numeric
prove: Frequency count, numeric
yrs: Frequency count, numeric
etc: Frequency count, numeric
investig: Frequency count, numeric
sell: Frequency count, numeric
cuz: Frequency count, numeric
hubbi: Frequency count, numeric
power: Frequency count, numeric
rare: Frequency count, numeric
poorcustomerservic: Frequency count, numeric
forth: Frequency count, numeric
multipl: Frequency count, numeric
angri: Frequency count, numeric
lake: Frequency count, numeric
consist: Frequency count, numeric
commit: Frequency count, numeric
merger: Frequency count, numeric
glitch: Frequency count, numeric
mainten: Frequency count, numeric
state: Frequency count, numeric
truth: Frequency count, numeric
unfriend: Frequency count, numeric
ill: Frequency count, numeric
level: Frequency count, numeric
lufthansa: Frequency count, numeric
replac: Frequency count, numeric
sick: Frequency count, numeric
typic: Frequency count, numeric
prompt: Frequency count, numeric
simpli: Frequency count, numeric
twice: Frequency count, numeric
hate: Frequency count, numeric
orf: Frequency count, numeric
driven: Frequency count, numeric
uauau: Frequency count, numeric
age: Frequency count, numeric
choos: Frequency count, numeric
poorservic: Frequency count, numeric
general: Frequency count, numeric
attent: Frequency count, numeric
lit: Frequency count, numeric
aspen: Frequency count, numeric
certain: Frequency count, numeric
florida: Frequency count, numeric
recov: Frequency count, numeric
allow: Frequency count, numeric
overweight: Frequency count, numeric
measur: Frequency count, numeric
woman: Frequency count, numeric
miser: Frequency count, numeric
block: Frequency count, numeric
dming: Frequency count, numeric
articl: Frequency count, numeric
redeem: Frequency count, numeric
ton: Frequency count, numeric
what: Frequency count, numeric
gain: Frequency count, numeric
musician: Frequency count, numeric
holder: Frequency count, numeric
whose: Frequency count, numeric
blog: Frequency count, numeric
cleveland: Frequency count, numeric
sunday: Frequency count, numeric
basic: Frequency count, numeric
assign: Frequency count, numeric
sens: Frequency count, numeric
doesnut: Frequency count, numeric
english: Frequency count, numeric
hassl: Frequency count, numeric
badservic: Frequency count, numeric
whatev: Frequency count, numeric
london: Frequency count, numeric
cute: Frequency count, numeric
kind: Frequency count, numeric
speed: Frequency count, numeric
cowork: Frequency count, numeric
hell: Frequency count, numeric
flightst: Frequency count, numeric
settl: Frequency count, numeric
rdu: Frequency count, numeric
shop: Frequency count, numeric
onboard: Frequency count, numeric
pts: Frequency count, numeric
compar: Frequency count, numeric
mex: Frequency count, numeric
ten: Frequency count, numeric
usairway: Frequency count, numeric
usairwaysfail: Frequency count, numeric
practic: Frequency count, numeric
occur: Frequency count, numeric
outsourc: Frequency count, numeric
collect: Frequency count, numeric
suggest: Frequency count, numeric
formal: Frequency count, numeric
handler: Frequency count, numeric
bridg: Frequency count, numeric
freez: Frequency count, numeric
temp: Frequency count, numeric
foot: Frequency count, numeric
broke: Frequency count, numeric
global: Frequency count, numeric
yyz: Frequency count, numeric
piss: Frequency count, numeric
engin: Frequency count, numeric
deplan: Frequency count, numeric
releas: Frequency count, numeric
advertis: Frequency count, numeric
extend: Frequency count, numeric
aircanada: Frequency count, numeric
lesson: Frequency count, numeric
written: Frequency count, numeric
pray: Frequency count, numeric
chair: Frequency count, numeric
meal: Frequency count, numeric
unreal: Frequency count, numeric
costum: Frequency count, numeric
understaf: Frequency count, numeric
beer: Frequency count, numeric
understood: Frequency count, numeric
oop: Frequency count, numeric
crazi: Frequency count, numeric
rob: Frequency count, numeric
shut: Frequency count, numeric
worthless: Frequency count, numeric
polic: Frequency count, numeric
clean: Frequency count, numeric
dri: Frequency count, numeric
msg: Frequency count, numeric
wet: Frequency count, numeric
piec: Frequency count, numeric
print: Frequency count, numeric
airway: Frequency count, numeric
mci: Frequency count, numeric
segment: Frequency count, numeric
slight: Frequency count, numeric
acct: Frequency count, numeric
eta: Frequency count, numeric
btv: Frequency count, numeric
cun: Frequency count, numeric
nite: Frequency count, numeric
worstcustomerservic: Frequency count, numeric
rerout: Frequency count, numeric
cri: Frequency count, numeric
garbag: Frequency count, numeric
epic: Frequency count, numeric
jetway: Frequency count, numeric
reagan: Frequency count, numeric
ber: Frequency count, numeric
till: Frequency count, numeric
frankfurt: Frequency count, numeric
fan: Frequency count, numeric
doubl: Frequency count, numeric
lisa: Frequency count, numeric
breakfast: Frequency count, numeric
irrit: Frequency count, numeric
humor: Frequency count, numeric
copi: Frequency count, numeric
ual: Frequency count, numeric
tampa: Frequency count, numeric
robot: Frequency count, numeric
visit: Frequency count, numeric
wear: Frequency count, numeric
grr: Frequency count, numeric
raleigh: Frequency count, numeric
terri: Frequency count, numeric
freq: Frequency count, numeric
rsw: Frequency count, numeric
lousi: Frequency count, numeric
fault: Frequency count, numeric
honeymoon: Frequency count, numeric
gotten: Frequency count, numeric
epicfail: Frequency count, numeric
awar: Frequency count, numeric
hilari: Frequency count, numeric
ktn: Frequency count, numeric
wreck: Frequency count, numeric
offici: Frequency count, numeric
pleasant: Frequency count, numeric
acknowledg: Frequency count, numeric
dot: Frequency count, numeric
brother: Frequency count, numeric
hous: Frequency count, numeric
pleasur: Frequency count, numeric
bdl: Frequency count, numeric
explor: Frequency count, numeric
facebook: Frequency count, numeric
tue: Frequency count, numeric
buf: Frequency count, numeric
downgrad: Frequency count, numeric
nashvill: Frequency count, numeric
surpris: Frequency count, numeric
freak: Frequency count, numeric
snowi: Frequency count, numeric
ineffici: Frequency count, numeric
tini: Frequency count, numeric
csr: Frequency count, numeric
dozen: Frequency count, numeric
kiosk: Frequency count, numeric
patienc: Frequency count, numeric
bus: Frequency count, numeric
prob: Frequency count, numeric
disgrac: Frequency count, numeric
hit: Frequency count, numeric
forev: Frequency count, numeric
tone: Frequency count, numeric
worker: Frequency count, numeric
lazi: Frequency count, numeric
frozen: Frequency count, numeric
metal: Frequency count, numeric
truck: Frequency count, numeric
valu: Frequency count, numeric
fast: Frequency count, numeric
reconsid: Frequency count, numeric
attitud: Frequency count, numeric
respect: Frequency count, numeric
pat: Frequency count, numeric
disgust: Frequency count, numeric
restor: Frequency count, numeric
worstairlineev: Frequency count, numeric
valuabl: Frequency count, numeric
park: Frequency count, numeric
desper: Frequency count, numeric
girlfriend: Frequency count, numeric
fraud: Frequency count, numeric
pretzel: Frequency count, numeric
lower: Frequency count, numeric
crappi: Frequency count, numeric
legal: Frequency count, numeric
hang: Frequency count, numeric
intent: Frequency count, numeric
felt: Frequency count, numeric
higher: Frequency count, numeric
qualiti: Frequency count, numeric
spanish: Frequency count, numeric
mech: Frequency count, numeric
retriev: Frequency count, numeric
except: Frequency count, numeric
contract: Frequency count, numeric
pvd: Frequency count, numeric
upcom: Frequency count, numeric
cover: Frequency count, numeric
dumb: Frequency count, numeric
hurt: Frequency count, numeric
won: Frequency count, numeric
memori: Frequency count, numeric
circumst: Frequency count, numeric
disconnect: Frequency count, numeric
reliabl: Frequency count, numeric
none: Frequency count, numeric
relat: Frequency count, numeric
act: Frequency count, numeric
organ: Frequency count, numeric
bay: Frequency count, numeric
import: Frequency count, numeric
describ: Frequency count, numeric
flightawar: Frequency count, numeric
per: Frequency count, numeric
tail: Frequency count, numeric
dinner: Frequency count, numeric
honest: Frequency count, numeric
capt: Frequency count, numeric
explan: Frequency count, numeric
cab: Frequency count, numeric
pit: Frequency count, numeric
dont: Frequency count, numeric
cheap: Frequency count, numeric
worstairlin: Frequency count, numeric
bummer: Frequency count, numeric
content: Frequency count, numeric
realiz: Frequency count, numeric
discov: Frequency count, numeric
ive: Frequency count, numeric
bhm: Frequency count, numeric
god: Frequency count, numeric
educ: Frequency count, numeric
volunt: Frequency count, numeric
philippin: Frequency count, numeric
aisl: Frequency count, numeric
drunk: Frequency count, numeric
log: Frequency count, numeric
strike: Frequency count, numeric
social: Frequency count, numeric
planet: Frequency count, numeric
hdn: Frequency count, numeric
concours: Frequency count, numeric
shuttl: Frequency count, numeric
known: Frequency count, numeric
sight: Frequency count, numeric
trap: Frequency count, numeric
numer: Frequency count, numeric
slept: Frequency count, numeric
prior: Frequency count, numeric
runway: Frequency count, numeric
fals: Frequency count, numeric
idiot: Frequency count, numeric
relationship: Frequency count, numeric
everytim: Frequency count, numeric
green: Frequency count, numeric
present: Frequency count, numeric
faa: Frequency count, numeric
suit: Frequency count, numeric
elit: Frequency count, numeric
staralli: Frequency count, numeric
sister: Frequency count, numeric
true: Frequency count, numeric
live: Frequency count, numeric
five: Frequency count, numeric
push: Frequency count, numeric
ass: Frequency count, numeric
sometim: Frequency count, numeric
stt: Frequency count, numeric
separ: Frequency count, numeric
often: Frequency count, numeric
bathroom: Frequency count, numeric
unitedsuck: Frequency count, numeric
toddler: Frequency count, numeric
competitor: Frequency count, numeric
pend: Frequency count, numeric
toilet: Frequency count, numeric
outrag: Frequency count, numeric
chi: Frequency count, numeric
safe: Frequency count, numeric
proof: Frequency count, numeric
automat: Frequency count, numeric
cater: Frequency count, numeric
tvs: Frequency count, numeric
overs: Frequency count, numeric
rent: Frequency count, numeric
cluster: Frequency count, numeric
confer: Frequency count, numeric
memphi: Frequency count, numeric
notifi: Frequency count, numeric
bereav: Frequency count, numeric
discount: Frequency count, numeric
funer: Frequency count, numeric
meant: Frequency count, numeric
passport: Frequency count, numeric
approach: Frequency count, numeric
rapid: Frequency count, numeric
tick: Frequency count, numeric
appal: Frequency count, numeric
journey: Frequency count, numeric
spell: Frequency count, numeric
perhap: Frequency count, numeric
ahold: Frequency count, numeric
delet: Frequency count, numeric
notch: Frequency count, numeric
cvg: Frequency count, numeric
shoulder: Frequency count, numeric
skill: Frequency count, numeric
allianc: Frequency count, numeric
belong: Frequency count, numeric
depend: Frequency count, numeric
star: Frequency count, numeric
staf: Frequency count, numeric
hospit: Frequency count, numeric
juan: Frequency count, numeric
personnel: Frequency count, numeric
particular: Frequency count, numeric
fam: Frequency count, numeric
pricey: Frequency count, numeric
unitedfail: Frequency count, numeric
inexcus: Frequency count, numeric
million: Frequency count, numeric
immedi: Frequency count, numeric
weight: Frequency count, numeric
arrang: Frequency count, numeric
condit: Frequency count, numeric
guarante: Frequency count, numeric
albani: Frequency count, numeric
peanut: Frequency count, numeric
clarifi: Frequency count, numeric
unknown: Frequency count, numeric
wed: Frequency count, numeric
ramp: Frequency count, numeric
cranki: Frequency count, numeric
hello: Frequency count, numeric
detroit: Frequency count, numeric
bush: Frequency count, numeric
cle: Frequency count, numeric
alright: Frequency count, numeric
especi: Frequency count, numeric
shitti: Frequency count, numeric
amount: Frequency count, numeric
tremend: Frequency count, numeric
averag: Frequency count, numeric
abysm: Frequency count, numeric
unbeliev: Frequency count, numeric
decid: Frequency count, numeric
mark: Frequency count, numeric
children: Frequency count, numeric
draw: Frequency count, numeric
roundtrip: Frequency count, numeric
loyalti: Frequency count, numeric
perk: Frequency count, numeric
download: Frequency count, numeric
hnl: Frequency count, numeric
cxl: Frequency count, numeric
progress: Frequency count, numeric
fiasco: Frequency count, numeric
callback: Frequency count, numeric
corpor: Frequency count, numeric
relax: Frequency count, numeric
mother: Frequency count, numeric
natur: Frequency count, numeric
wasnt: Frequency count, numeric
proud: Frequency count, numeric
water: Frequency count, numeric
legroom: Frequency count, numeric
rest: Frequency count, numeric
cooki: Frequency count, numeric
chose: Frequency count, numeric
young: Frequency count, numeric
tmrw: Frequency count, numeric
weird: Frequency count, numeric
stream: Frequency count, numeric
decent: Frequency count, numeric
merg: Frequency count, numeric
pound: Frequency count, numeric
fire: Frequency count, numeric
blow: Frequency count, numeric
eventu: Frequency count, numeric
pain: Frequency count, numeric
cnn: Frequency count, numeric
approv: Frequency count, numeric
flts: Frequency count, numeric
ship: Frequency count, numeric
similar: Frequency count, numeric
inch: Frequency count, numeric
couldnt: Frequency count, numeric
south: Frequency count, numeric
six: Frequency count, numeric
directtv: Frequency count, numeric
advic: Frequency count, numeric
closer: Frequency count, numeric
traffic: Frequency count, numeric
beliz: Frequency count, numeric
unlik: Frequency count, numeric
congratul: Frequency count, numeric
airbus: Frequency count, numeric
wall: Frequency count, numeric
shout: Frequency count, numeric
disregard: Frequency count, numeric
dragon: Frequency count, numeric
pen: Frequency count, numeric
backup: Frequency count, numeric
remain: Frequency count, numeric
bna: Frequency count, numeric
jax: Frequency count, numeric
exit: Frequency count, numeric
wheelchair: Frequency count, numeric
plenti: Frequency count, numeric
yay: Frequency count, numeric
fra: Frequency count, numeric
die: Frequency count, numeric
plastic: Frequency count, numeric
stock: Frequency count, numeric
roc: Frequency count, numeric
orlean: Frequency count, numeric
map: Frequency count, numeric
insult: Frequency count, numeric
north: Frequency count, numeric
sale: Frequency count, numeric
tkt: Frequency count, numeric
smile: Frequency count, numeric
ind: Frequency count, numeric
interview: Frequency count, numeric
biggest: Frequency count, numeric
ripoff: Frequency count, numeric
although: Frequency count, numeric
difficulti: Frequency count, numeric
nothappi: Frequency count, numeric
celebr: Frequency count, numeric
slc: Frequency count, numeric
argu: Frequency count, numeric
histori: Frequency count, numeric
overal: Frequency count, numeric
expedia: Frequency count, numeric
document: Frequency count, numeric
technic: Frequency count, numeric
login: Frequency count, numeric
incent: Frequency count, numeric
bahama: Frequency count, numeric
horrend: Frequency count, numeric
procedur: Frequency count, numeric
parti: Frequency count, numeric
cell: Frequency count, numeric
teach: Frequency count, numeric
isnt: Frequency count, numeric
tpa: Frequency count, numeric
msp: Frequency count, numeric
chariti: Frequency count, numeric
aviat: Frequency count, numeric
cup: Frequency count, numeric
extens: Frequency count, numeric
somebodi: Frequency count, numeric
john: Frequency count, numeric
verifi: Frequency count, numeric
furious: Frequency count, numeric
bankrupt: Frequency count, numeric
iuv: Frequency count, numeric
type: Frequency count, numeric
googl: Frequency count, numeric
cart: Frequency count, numeric
golf: Frequency count, numeric
signific: Frequency count, numeric
insan: Frequency count, numeric
remot: Frequency count, numeric
volum: Frequency count, numeric
patient: Frequency count, numeric
folder: Frequency count, numeric
darn: Frequency count, numeric
tight: Frequency count, numeric
clarif: Frequency count, numeric
east: Frequency count, numeric
embarrass: Frequency count, numeric
warn: Frequency count, numeric
wednesday: Frequency count, numeric
combin: Frequency count, numeric
res: Frequency count, numeric
snack: Frequency count, numeric
belt: Frequency count, numeric
autom: Frequency count, numeric
transport: Frequency count, numeric
mad: Frequency count, numeric
june: Frequency count, numeric
specif: Frequency count, numeric
function: Frequency count, numeric
lavatori: Frequency count, numeric
winner: Frequency count, numeric
roll: Frequency count, numeric
accur: Frequency count, numeric
companion: Frequency count, numeric
necessari: Frequency count, numeric
thousand: Frequency count, numeric
pbi: Frequency count, numeric
father: Frequency count, numeric
lifetim: Frequency count, numeric
burn: Frequency count, numeric
misplac: Frequency count, numeric
laguardia: Frequency count, numeric
size: Frequency count, numeric
box: Frequency count, numeric
haha: Frequency count, numeric
donat: Frequency count, numeric
wth: Frequency count, numeric
hungri: Frequency count, numeric
maint: Frequency count, numeric
firstclass: Frequency count, numeric
massiv: Frequency count, numeric
fantast: Frequency count, numeric
annual: Frequency count, numeric
exchang: Frequency count, numeric
cont: Frequency count, numeric
dial: Frequency count, numeric
tablet: Frequency count, numeric
courteous: Frequency count, numeric
yup: Frequency count, numeric
alert: Frequency count, numeric
fave: Frequency count, numeric
dest: Frequency count, numeric
straight: Frequency count, numeric
anniversari: Frequency count, numeric
expedit: Frequency count, numeric
awe: Frequency count, numeric
buffalo: Frequency count, numeric
estim: Frequency count, numeric
join: Frequency count, numeric
gas: Frequency count, numeric
sept: Frequency count, numeric
magic: Frequency count, numeric
nasti: Frequency count, numeric
admir: Frequency count, numeric
customerservicefail: Frequency count, numeric
heavi: Frequency count, numeric
incom: Frequency count, numeric
stick: Frequency count, numeric
survey: Frequency count, numeric
rant: Frequency count, numeric
puerto: Frequency count, numeric
rico: Frequency count, numeric
annricord: Frequency count, numeric
alot: Frequency count, numeric
pet: Frequency count, numeric
west: Frequency count, numeric
admit: Frequency count, numeric
boss: Frequency count, numeric
women: Frequency count, numeric
waiver: Frequency count, numeric
incorrect: Frequency count, numeric
dobett: Frequency count, numeric
weigh: Frequency count, numeric
whether: Frequency count, numeric
wrote: Frequency count, numeric
custserv: Frequency count, numeric
parent: Frequency count, numeric
term: Frequency count, numeric
camera: Frequency count, numeric
didnut: Frequency count, numeric
pittsburgh: Frequency count, numeric
tab: Frequency count, numeric
harder: Frequency count, numeric
van: Frequency count, numeric
somewher: Frequency count, numeric
rush: Frequency count, numeric
letter: Frequency count, numeric
fresh: Frequency count, numeric
mission: Frequency count, numeric
subpar: Frequency count, numeric
ric: Frequency count, numeric
your: Frequency count, numeric
august: Frequency count, numeric
reward: Frequency count, numeric
headach: Frequency count, numeric
conflict: Frequency count, numeric
pref: Frequency count, numeric
fort: Frequency count, numeric
invit: Frequency count, numeric
flytpa: Frequency count, numeric
protect: Frequency count, numeric
neither: Frequency count, numeric
laugh: Frequency count, numeric
scale: Frequency count, numeric
nonexist: Frequency count, numeric
blah: Frequency count, numeric
tear: Frequency count, numeric
hartford: Frequency count, numeric
mke: Frequency count, numeric
warm: Frequency count, numeric
odd: Frequency count, numeric
packag: Frequency count, numeric
omaha: Frequency count, numeric
initi: Frequency count, numeric
lauderdal: Frequency count, numeric
lmao: Frequency count, numeric
feed: Frequency count, numeric
earth: Frequency count, numeric
fortun: Frequency count, numeric
heart: Frequency count, numeric
dang: Frequency count, numeric
ici: Frequency count, numeric
magazin: Frequency count, numeric
weur: Frequency count, numeric
greatservic: Frequency count, numeric
rno: Frequency count, numeric
street: Frequency count, numeric
nexus: Frequency count, numeric
cheat: Frequency count, numeric
inde: Frequency count, numeric
there: Frequency count, numeric
qualifi: Frequency count, numeric
asham: Frequency count, numeric
speedi: Frequency count, numeric
success: Frequency count, numeric
gogo: Frequency count, numeric
hub: Frequency count, numeric
dime: Frequency count, numeric
disorgan: Frequency count, numeric
sigh: Frequency count, numeric
proactiv: Frequency count, numeric
phx: Frequency count, numeric
jacksonvill: Frequency count, numeric
drove: Frequency count, numeric
birmingham: Frequency count, numeric
brutal: Frequency count, numeric
midway: Frequency count, numeric
swa: Frequency count, numeric
ivr: Frequency count, numeric
proceed: Frequency count, numeric
spiritairlin: Frequency count, numeric
data: Frequency count, numeric
southwestairlin: Frequency count, numeric
phlairport: Frequency count, numeric
charleston: Frequency count, numeric
throughout: Frequency count, numeric
birth: Frequency count, numeric
gear: Frequency count, numeric
nonprofit: Frequency count, numeric
partnership: Frequency count, numeric
mdw: Frequency count, numeric
fell: Frequency count, numeric
destinationdragon: Frequency count, numeric
uisouthwestair: Frequency count, numeric
imaginedragon: Frequency count, numeric
voic: Frequency count, numeric
profession: Frequency count, numeric
unreli: Frequency count, numeric
test: Frequency count, numeric
featur: Frequency count, numeric
bae: Frequency count, numeric
contest: Frequency count, numeric
spirit: Frequency count, numeric
hunt: Frequency count, numeric
scaveng: Frequency count, numeric
injuri: Frequency count, numeric
hero: Frequency count, numeric
grate: Frequency count, numeric
est: Frequency count, numeric
reflect: Frequency count, numeric
station: Frequency count, numeric
antonio: Frequency count, numeric
noon: Frequency count, numeric
ohio: Frequency count, numeric
aug: Frequency count, numeric
columbus: Frequency count, numeric
oakland: Frequency count, numeric
bostonlogan: Frequency count, numeric
heavili: Frequency count, numeric
enrout: Frequency count, numeric
soak: Frequency count, numeric
rethink: Frequency count, numeric
stroller: Frequency count, numeric
athlet: Frequency count, numeric
aka: Frequency count, numeric
telephon: Frequency count, numeric
band: Frequency count, numeric
ring: Frequency count, numeric
color: Frequency count, numeric
compass: Frequency count, numeric
lucki: Frequency count, numeric
jamaica: Frequency count, numeric
loss: Frequency count, numeric
cali: Frequency count, numeric
sunni: Frequency count, numeric
harbor: Frequency count, numeric
batteri: Frequency count, numeric
baltimor: Frequency count, numeric
greenvill: Frequency count, numeric
usair: Frequency count, numeric
indi: Frequency count, numeric
northeast: Frequency count, numeric
cmon: Frequency count, numeric
loos: Frequency count, numeric
spoken: Frequency count, numeric
heck: Frequency count, numeric
colleagu: Frequency count, numeric
resch: Frequency count, numeric
louisvill: Frequency count, numeric
blue: Frequency count, numeric
fortunemagazin: Frequency count, numeric
lunch: Frequency count, numeric
anxious: Frequency count, numeric
inclement: Frequency count, numeric
gari: Frequency count, numeric
kelli: Frequency count, numeric
stupid: Frequency count, numeric
summer: Frequency count, numeric
cash: Frequency count, numeric
crowd: Frequency count, numeric
utah: Frequency count, numeric
velourl: Frequency count, numeric
triflight: Frequency count, numeric
steal: Frequency count, numeric
selfi: Frequency count, numeric
paypal: Frequency count, numeric
nearbi: Frequency count, numeric
pwm: Frequency count, numeric
aww: Frequency count, numeric
colleg: Frequency count, numeric
physic: Frequency count, numeric
savannah: Frequency count, numeric
anticip: Frequency count, numeric
uuuu: Frequency count, numeric
lauren: Frequency count, numeric
lovedragonss: Frequency count, numeric
costa: Frequency count, numeric
rica: Frequency count, numeric
chao: Frequency count, numeric
unload: Frequency count, numeric
pump: Frequency count, numeric
evalu: Frequency count, numeric
predict: Frequency count, numeric
disney: Frequency count, numeric
dealt: Frequency count, numeric
fastest: Frequency count, numeric
involv: Frequency count, numeric
regular: Frequency count, numeric
lodg: Frequency count, numeric
caller: Frequency count, numeric
nation: Frequency count, numeric
sju: Frequency count, numeric
fleek: Frequency count, numeric
trueblu: Frequency count, numeric
uijetblu: Frequency count, numeric
plat: Frequency count, numeric
beach: Frequency count, numeric
flyfi: Frequency count, numeric
viequ: Frequency count, numeric
njb: Frequency count, numeric
jblu: Frequency count, numeric
stole: Frequency count, numeric
wsj: Frequency count, numeric
barbado: Frequency count, numeric
cuba: Frequency count, numeric
reli: Frequency count, numeric
agenc: Frequency count, numeric
mem: Frequency count, numeric
appeas: Frequency count, numeric
republican: Frequency count, numeric
waterburi: Frequency count, numeric
flyingitforward: Frequency count, numeric
mint: Frequency count, numeric
nantucket: Frequency count, numeric
glass: Frequency count, numeric
mosaic: Frequency count, numeric
goodwil: Frequency count, numeric
getittogeth: Frequency count, numeric
endless: Frequency count, numeric
brandmanc: Frequency count, numeric
hpn: Frequency count, numeric
prais: Frequency count, numeric
circl: Frequency count, numeric
journal: Frequency count, numeric
sxm: Frequency count, numeric
asleep: Frequency count, numeric
blueman: Frequency count, numeric
digit: Frequency count, numeric
flyitforward: Frequency count, numeric
crewmemb: Frequency count, numeric
liveri: Frequency count, numeric
bottl: Frequency count, numeric
divers: Frequency count, numeric
dissatisfi: Frequency count, numeric
comm: Frequency count, numeric
dump: Frequency count, numeric
paint: Frequency count, numeric
shoutout: Frequency count, numeric
alaska: Frequency count, numeric
weull: Frequency count, numeric
jvmchat: Frequency count, numeric
sympathi: Frequency count, numeric
dividend: Frequency count, numeric
chairman: Frequency count, numeric
uiusairway: Frequency count, numeric
exec: Frequency count, numeric
ctl: Frequency count, numeric
flydelta: Frequency count, numeric
logist: Frequency count, numeric
sexual: Frequency count, numeric
fear: Frequency count, numeric
aadvantag: Frequency count, numeric
cot: Frequency count, numeric
key: Frequency count, numeric
usairwayssuck: Frequency count, numeric
med: Frequency count, numeric
vile: Frequency count, numeric
uii: Frequency count, numeric
uiamericanair: Frequency count, numeric
assult: Frequency count, numeric
dfwairport: Frequency count, numeric
filmcrew: Frequency count, numeric
cowboycerron: Frequency count, numeric
americanview: Frequency count, numeric

Details

The data provided here is an altered and cleaned version version of the original source.

Source

https://www.figure-eight.com/data-for-everyone/

Package 'fastNaiveBayes'

Help Index

Fast Naive Bayes Classifier for different Distributions

Description

Usage

Arguments

Details

Value

See Also

Examples

Distribution Detection Function

Description

Usage

Arguments

Details

Value

Examples

Save & Load Function for Fast Naive Bayes Models

Description

Usage

Arguments

Value

Examples

Update function

Description

Usage

Arguments

Predict Method for fastNaiveBayes fits

Description

Usage

Arguments

Value

See Also

This data originally came from Crowdflower's Data for Everyone library.

Description

Usage

Format

Details

Source

This data originally came from Crowdflower's Data for Everyone library.

Description

Usage

Format

Details

Source