pyTweetBot.learning package

Submodules

pyTweetBot.learning.CensorModel module

class pyTweetBot.learning.CensorModel.CensorModel(config)

Bases: object

Forbidden words classifier

static load_censor(config)

Load a complete model and censor with path to model :param config: :return:

pyTweetBot.learning.Classifier module

pyTweetBot.learning.Dataset module

class pyTweetBot.learning.Dataset.Dataset

Bases: object

A dataset of URL and title for training

add_negative(text)

Add a positive sample :param text: :return:

add_positive(text)

Add a positive sample :param text: :return:

data

Data :return:

get_texts()

Get texts :return:

is_in(ttext)

Is in dataset? :param ttext: :return:

static load(opt)

Load the model from DB or file :param opt: Loading option :return: The model class

next()

Next element :return:

save(filename)

Save the dataset :param filename:

targets

Targets :return:

to_json()

To JSON :return:

pyTweetBot.learning.DecisionTree module

pyTweetBot.learning.Model module

pyTweetBot.learning.NaiveBayesClassifier module

Module contents

class pyTweetBot.learning.CensorModel(config)

Bases: object

Forbidden words classifier

static load_censor(config)

Load a complete model and censor with path to model :param config: :return:

class pyTweetBot.learning.Dataset

Bases: object

A dataset of URL and title for training

add_negative(text)

Add a positive sample :param text: :return:

add_positive(text)

Add a positive sample :param text: :return:

data

Data :return:

get_texts()

Get texts :return:

is_in(ttext)

Is in dataset? :param ttext: :return:

static load(opt)

Load the model from DB or file :param opt: Loading option :return: The model class

next()

Next element :return:

save(filename)

Save the dataset :param filename:

targets

Targets :return:

to_json()

To JSON :return: