Namespace for algorithm classes. More...

Classes
class	AllTokens
	Counts all tokens in a corpus. More...

class	Assoc
	Empty algorithm template. More...

class	AssocOverTime
	Empty algorithm template. More...

class	CorpusGenerator
	Algorithm building a text corpus and creating corpus statistics from the input data. More...

class	Empty
	Empty algorithm template. More...

class	ExtractIds
	Extracts the parsed IDs from a filtered corpus. More...

class	SentimentOverTime
	Sentiment analysis using the VADER algorithm. More...

class	TermsOverTime
	Algorithm counting specific terms in a text corpus over time. More...

class	TopicModelling
	Topic Modeller. More...

class	WordsOverTime
	Counts the occurrence of articles, sentences, and tokens in a corpus over time. More...

Typedefs
using	AlgoThreadProperties = Struct::AlgoThreadProperties

using	AlgoThreadPtr = std::unique_ptr< Module::Analyzer::Thread >

Registration
AlgoThreadPtr	initAlgo (const AlgoThreadProperties &thread)
	Creates an algorithm thread. More...

Constants
constexpr auto	allTokensColumns {2}
	The number of columns in the tokens table. More...

constexpr auto	allTokensUpdateEveryDate {100U}
	Indicates after how many dates the status will be updated, if a date map is available. More...

constexpr auto	allTokensUpdateEveryArticle {1000U}
	Indicates after how many articles the status will be updated, if no date map, but an article map is available. More...

constexpr auto	allTokensUpdateEveryToken {10000U}
	Indicates after how many tokens the status will be updated, if no date and no article map is available. More...

constexpr auto	allTokensUpdateEveryRow {1000U}
	Indicates after how many rows the status will be updated while saving the results to the database. More...

constexpr auto	assocUpdateProgressEvery {1000}
	Indicates, while saving, after how many articles the progress of the thread will be updated. More...

constexpr auto	assocAddColumns {2}
	Number of extra columns included in a dataset (except date). More...

constexpr auto	assocMinColumns {assocAddColumns + 1 }
	Minimum number of columns included in a dataset (including date). More...

constexpr auto	assocOverTimeUpdateProgressEvery {100}
	Indicates, while saving, after how many rows the progress of the thread will be updated. More...

constexpr auto	assocOverTimeAddColumns {2}
	Number of extra columns included in a dataset (except date). More...

constexpr auto	assocOverTimeMinColumns {assocOverTimeAddColumns + 1 }
	Minimum number of columns included in a dataset (including date). More...

constexpr auto	corpusNumFields {9}
	Number of target fields. More...

constexpr auto	extractIdsUpdateProgressEvery {1000}
	Indicates after how many articles the progress of the thread will be updated. More...

constexpr auto	sentimentUpdateCalculateProgressEvery {250000}
	Indicates, while calculating, after how many sentences the progress of the thread will be updated. More...

constexpr auto	sentimentUpdateSavingProgressEvery {10}
	Indicates, while saving, after how many rows the progress of the thread will be updated. More...

constexpr auto	sentimentMinNumColumns {1}
	Number of default columns to be written to the target table. More...

constexpr auto	sentimentMinColumnsPerCategory {2}
	Number of columns per category if article-based sentiment is deactivated. More...

constexpr auto	sentimentArticleColumnsPerCategory {4}
	Number of columns per category if article-based sentiment is activated. More...

constexpr auto	sentimentDefaultThreshold {10}
	The default threshold (sentiments lower than that number will be ignored). More...

constexpr auto	sentimentDictionary {"sentiment-en"sv}
	The default sentiment dictionary to be used. More...

constexpr auto	sentimentEmojis {"emojis-en"sv}
	The default emoji dictionary to be used. More...

constexpr auto	sentimentPercentageFactor {100.F}
	Factor to convert value to percentage. More...

constexpr auto	topicModellingDirectory {"mdl"sv}
	The directory for model files. More...

constexpr auto	topicModellingDefaultNumberOfTopics {2}
	The default number of initial topics. More...

constexpr auto	topicModellingDefaultNumberOfTopicTokens {5}
	The default number of most-probable tokens for each detected topic. More...

constexpr auto	topicModellingDefaultBurnIn {100}
	The default number of burn-in iterations. More...

constexpr auto	topicModellingDefaultIterations {1000}
	The default number of iterations to train the model. More...

constexpr auto	topicModellingDefaultIterationsAtOnce {25}
	The default number of iterations to train the model at once. More...

constexpr auto	topicModellingDefaultMinCf {1}
	The default number of a token's minimum frequency in the corpus. More...

constexpr auto	topicModellingDefaultMinDf {1}
	The default number of a token's minimum document frequency. More...

constexpr auto	topicModellingDefaultOptimizeEvery {10}
	The default optimization interval for the model parameters, in training iterations. More...

constexpr auto	topicModellingDefaultRemoveTopN {0}
	The default number of most-common tokens to ignore. More...

constexpr auto	topicModellingDefaultNumberOfThreads {1}
	The default number of threads for training the model. More...

constexpr auto	topicModellingDefaultAlpha {0.1F}
	The default initial hyperparameter for the Dirichlet distribution for document–table. More...

constexpr auto	topicModellingDefaultConversionThreshold {0.F}
	The default threshold for topics to be included when converting a HDP to a LDA model. More...

constexpr auto	topicModellingDefaultEta {0.01F}
	The default initial hyperparameter for the Dirichlet distribution for topic–token. More...

constexpr auto	topicModellingDefaultGamma {0.1F}
	The default initial concentration coefficient of the Dirichlet Process for table–topic. More...

constexpr auto	topicModellingDefaultDocIterations {100}
	The default number of maximum iterations to classify a document. More...

constexpr auto	topicModellingDefaultNumberOfWorkers {0}
	The default number of worker threads for infering the topics of articles. More...

constexpr auto	topicModellingDefaultMinLabelCf {1}
	The default number of a topic label's minimum frequency in the corpus. More...

constexpr auto	topicModellingDefaultMinLabelDf {1}
	The default number of a topic label's minimum document frequency. More...

constexpr auto	topicModellingDefaultMinLabelLength {2}
	The default minimum length of topic labels, in tokens. More...

constexpr auto	topicModellingDefaultMaxLabelLength {5}
	The default maximum length of topic labels, in tokens. More...

constexpr auto	topicModellingDefaultMaxLabelCandidates {10000}
	The default maximum number of topic label candidates to be extracted from the training data. More...

constexpr auto	topicModellingDefaultLabelSmoothing {.1F}
	The default Laplace smoothing for the automated detection of topic labels. More...

constexpr auto	topicModellingDefaultLabelMu {.25F}
	The default discriminative coefficient for the automated detection of topic labels. More...

constexpr auto	topicModellingUpdateProgressEvery {1000}
	The number of added/saved articles after which the progress will be updated. More...

constexpr auto	topicModellingUpdateProgressEveryDocs {25}
	The number of classified documents after which the progress will be updated. More...

constexpr auto	topicModellingPrecisionLL {6}
	The number of digits of the log-likelihood to be logged. More...

constexpr auto	topicModellingTargetColumns {2}
	The number of additional columns in the target table. More...

constexpr auto	topicModellingTopicColumns {2}
	The number of additional columns in the topic table. More...

constexpr auto	topicModellingColumnsPerLabel {2}
	The number of columns per top label. More...

constexpr auto	topicModellingColumnsPerToken {2}
	The number of columns per top token. More...

constexpr auto	topicModellingPrecisionUlp {5}
	Precision used when testing topic probabilities for equality, in ULPs (units in the last place). More...

constexpr auto	wordsUpdateProgressEvery {100}
	Indicates after how many date groups the progress of the thread will be updated. More...

constexpr auto	wordsNumberOfColumns {4}
	The number of columns to write to the target table. More...

Detailed Description

Namespace for algorithm classes.

Typedef Documentation

◆ AlgoThreadProperties

using crawlservpp::Module::Analyzer::Algo::AlgoThreadProperties = typedef Struct::AlgoThreadProperties

◆ AlgoThreadPtr

using crawlservpp::Module::Analyzer::Algo::AlgoThreadPtr = typedef std::unique_ptr<Module::Analyzer::Thread>

Function Documentation

◆ initAlgo()

AlgoThreadPtr crawlservpp::Module::Analyzer::Algo::initAlgo ( const AlgoThreadProperties & thread )

Creates an algorithm thread.

Use the

REGISTER_ALGORITHM(ID, CLASS)

macro to register an algorithm class.

The macro will check the algorithm ID inside the given properties and return the pointer to a new algorithm thread if it matches the algorithm that has been registered using the macro.

Parameters

thread Constant reference to the properties of the algorithm thread to create.

Returns: The pointer to a new algorithm thread or nullptr if the algorithm ID specified in the given structure has not been registered.

References REGISTER_ALGORITHM.

Referenced by crawlservpp::Main::Server::tick().

Variable Documentation

◆ allTokensColumns

constexpr auto crawlservpp::Module::Analyzer::Algo::allTokensColumns {2}

inline

The number of columns in the tokens table.

Referenced by crawlservpp::Module::Analyzer::Algo::AllTokens::resetAlgo().

◆ allTokensUpdateEveryArticle

constexpr auto crawlservpp::Module::Analyzer::Algo::allTokensUpdateEveryArticle {1000U}

inline

Indicates after how many articles the status will be updated, if no date map, but an article map is available.

Referenced by crawlservpp::Module::Analyzer::Algo::AllTokens::onAlgoTick().

◆ allTokensUpdateEveryDate

constexpr auto crawlservpp::Module::Analyzer::Algo::allTokensUpdateEveryDate {100U}

inline

Indicates after how many dates the status will be updated, if a date map is available.

Referenced by crawlservpp::Module::Analyzer::Algo::AllTokens::onAlgoTick().

◆ allTokensUpdateEveryRow

constexpr auto crawlservpp::Module::Analyzer::Algo::allTokensUpdateEveryRow {1000U}

inline

Indicates after how many rows the status will be updated while saving the results to the database.

Referenced by crawlservpp::Module::Analyzer::Algo::AllTokens::resetAlgo().

◆ allTokensUpdateEveryToken

constexpr auto crawlservpp::Module::Analyzer::Algo::allTokensUpdateEveryToken {10000U}

inline

Indicates after how many tokens the status will be updated, if no date and no article map is available.

Referenced by crawlservpp::Module::Analyzer::Algo::AllTokens::onAlgoTick().

◆ assocAddColumns

constexpr auto crawlservpp::Module::Analyzer::Algo::assocAddColumns {2}

inline

Number of extra columns included in a dataset (except date).

◆ assocMinColumns

constexpr auto crawlservpp::Module::Analyzer::Algo::assocMinColumns {assocAddColumns + 1 }

inline

Minimum number of columns included in a dataset (including date).

Referenced by crawlservpp::Module::Analyzer::Algo::Assoc::onAlgoInitTarget(), and crawlservpp::Module::Analyzer::Algo::Assoc::resetAlgo().

◆ assocOverTimeAddColumns

constexpr auto crawlservpp::Module::Analyzer::Algo::assocOverTimeAddColumns {2}

inline

Number of extra columns included in a dataset (except date).

Referenced by crawlservpp::Module::Analyzer::Algo::AssocOverTime::resetAlgo().

◆ assocOverTimeMinColumns

constexpr auto crawlservpp::Module::Analyzer::Algo::assocOverTimeMinColumns {assocOverTimeAddColumns + 1 }

inline

Minimum number of columns included in a dataset (including date).

Referenced by crawlservpp::Module::Analyzer::Algo::AssocOverTime::onAlgoInitTarget(), and crawlservpp::Module::Analyzer::Algo::AssocOverTime::resetAlgo().

◆ assocOverTimeUpdateProgressEvery

constexpr auto crawlservpp::Module::Analyzer::Algo::assocOverTimeUpdateProgressEvery {100}

inline

Indicates, while saving, after how many rows the progress of the thread will be updated.

Referenced by crawlservpp::Module::Analyzer::Algo::AssocOverTime::resetAlgo().

◆ assocUpdateProgressEvery

constexpr auto crawlservpp::Module::Analyzer::Algo::assocUpdateProgressEvery {1000}

inline

Indicates, while saving, after how many articles the progress of the thread will be updated.

Referenced by crawlservpp::Module::Analyzer::Algo::Assoc::resetAlgo().

◆ corpusNumFields

constexpr auto crawlservpp::Module::Analyzer::Algo::corpusNumFields {9}

inline

Number of target fields.

Referenced by crawlservpp::Module::Analyzer::Algo::CorpusGenerator::onAlgoInit(), and crawlservpp::Module::Analyzer::Algo::CorpusGenerator::onAlgoInitTarget().

◆ extractIdsUpdateProgressEvery

constexpr auto crawlservpp::Module::Analyzer::Algo::extractIdsUpdateProgressEvery {1000}

inline

Indicates after how many articles the progress of the thread will be updated.

Referenced by crawlservpp::Module::Analyzer::Algo::ExtractIds::resetAlgo().

◆ sentimentArticleColumnsPerCategory

constexpr auto crawlservpp::Module::Analyzer::Algo::sentimentArticleColumnsPerCategory {4}

inline

Number of columns per category if article-based sentiment is activated.

Referenced by crawlservpp::Module::Analyzer::Algo::SentimentOverTime::onAlgoInitTarget(), and crawlservpp::Module::Analyzer::Algo::SentimentOverTime::resetAlgo().

◆ sentimentDefaultThreshold

constexpr auto crawlservpp::Module::Analyzer::Algo::sentimentDefaultThreshold {10}

inline

The default threshold (sentiments lower than that number will be ignored).

◆ sentimentDictionary

constexpr auto crawlservpp::Module::Analyzer::Algo::sentimentDictionary {"sentiment-en"sv}

inline

The default sentiment dictionary to be used.

◆ sentimentEmojis

constexpr auto crawlservpp::Module::Analyzer::Algo::sentimentEmojis {"emojis-en"sv}

inline

The default emoji dictionary to be used.

◆ sentimentMinColumnsPerCategory

constexpr auto crawlservpp::Module::Analyzer::Algo::sentimentMinColumnsPerCategory {2}

inline

Number of columns per category if article-based sentiment is deactivated.

Referenced by crawlservpp::Module::Analyzer::Algo::SentimentOverTime::onAlgoInitTarget(), and crawlservpp::Module::Analyzer::Algo::SentimentOverTime::resetAlgo().

◆ sentimentMinNumColumns

constexpr auto crawlservpp::Module::Analyzer::Algo::sentimentMinNumColumns {1}

inline

Number of default columns to be written to the target table.

Referenced by crawlservpp::Module::Analyzer::Algo::SentimentOverTime::onAlgoInitTarget(), and crawlservpp::Module::Analyzer::Algo::SentimentOverTime::resetAlgo().

◆ sentimentPercentageFactor

constexpr auto crawlservpp::Module::Analyzer::Algo::sentimentPercentageFactor {100.F}

inline

Factor to convert value to percentage.

Referenced by crawlservpp::Module::Analyzer::Algo::SentimentOverTime::resetAlgo().

◆ sentimentUpdateCalculateProgressEvery

constexpr auto crawlservpp::Module::Analyzer::Algo::sentimentUpdateCalculateProgressEvery {250000}

inline

Indicates, while calculating, after how many sentences the progress of the thread will be updated.

Referenced by crawlservpp::Module::Analyzer::Algo::SentimentOverTime::resetAlgo().

◆ sentimentUpdateSavingProgressEvery

constexpr auto crawlservpp::Module::Analyzer::Algo::sentimentUpdateSavingProgressEvery {10}

inline

Indicates, while saving, after how many rows the progress of the thread will be updated.

Referenced by crawlservpp::Module::Analyzer::Algo::SentimentOverTime::resetAlgo().

◆ topicModellingColumnsPerLabel

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingColumnsPerLabel {2}

inline

The number of columns per top label.

Referenced by crawlservpp::Module::Analyzer::Algo::TopicModelling::resetAlgo().

◆ topicModellingColumnsPerToken

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingColumnsPerToken {2}

inline

The number of columns per top token.

Referenced by crawlservpp::Module::Analyzer::Algo::TopicModelling::resetAlgo().

◆ topicModellingDefaultAlpha

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultAlpha {0.1F}

inline

The default initial hyperparameter for the Dirichlet distribution for document–table.

◆ topicModellingDefaultBurnIn

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultBurnIn {100}

inline

The default number of burn-in iterations.

"Burned in" iterations will be skipped before starting to train the model.

◆ topicModellingDefaultConversionThreshold

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultConversionThreshold {0.F}

inline

The default threshold for topics to be included when converting a HDP to a LDA model.

◆ topicModellingDefaultDocIterations

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultDocIterations {100}

inline

The default number of maximum iterations to classify a document.

◆ topicModellingDefaultEta

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultEta {0.01F}

inline

The default initial hyperparameter for the Dirichlet distribution for topic–token.

◆ topicModellingDefaultGamma

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultGamma {0.1F}

inline

The default initial concentration coefficient of the Dirichlet Process for table–topic.

Will be ignored, if the LDA instead of the HDP algorithm is used, i.e. a fixed number of topics is set.

◆ topicModellingDefaultIterations

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultIterations {1000}

inline

The default number of iterations to train the model.

◆ topicModellingDefaultIterationsAtOnce

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultIterationsAtOnce {25}

inline

The default number of iterations to train the model at once.

◆ topicModellingDefaultLabelMu

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultLabelMu {.25F}

inline

The default discriminative coefficient for the automated detection of topic labels.

◆ topicModellingDefaultLabelSmoothing

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultLabelSmoothing {.1F}

inline

The default Laplace smoothing for the automated detection of topic labels.

◆ topicModellingDefaultMaxLabelCandidates

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultMaxLabelCandidates {10000}

inline

The default maximum number of topic label candidates to be extracted from the training data.

◆ topicModellingDefaultMaxLabelLength

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultMaxLabelLength {5}

inline

The default maximum length of topic labels, in tokens.

◆ topicModellingDefaultMinCf

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultMinCf {1}

inline

The default number of a token's minimum frequency in the corpus.

◆ topicModellingDefaultMinDf

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultMinDf {1}

inline

The default number of a token's minimum document frequency.

◆ topicModellingDefaultMinLabelCf

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultMinLabelCf {1}

inline

The default number of a topic label's minimum frequency in the corpus.

◆ topicModellingDefaultMinLabelDf

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultMinLabelDf {1}

inline

The default number of a topic label's minimum document frequency.

◆ topicModellingDefaultMinLabelLength

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultMinLabelLength {2}

inline

The default minimum length of topic labels, in tokens.

◆ topicModellingDefaultNumberOfThreads

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultNumberOfThreads {1}

inline

The default number of threads for training the model.

◆ topicModellingDefaultNumberOfTopics

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultNumberOfTopics {2}

inline

The default number of initial topics.

Will be changed according to the data if the HDP (and not the LDA) algorithm is used, i.e. if the number of topics is not set to be fixed.

◆ topicModellingDefaultNumberOfTopicTokens

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultNumberOfTopicTokens {5}

inline

The default number of most-probable tokens for each detected topic.

This number of most-probable tokens for each detected topic will be written to the provided topic table.

◆ topicModellingDefaultNumberOfWorkers

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultNumberOfWorkers {0}

inline

The default number of worker threads for infering the topics of articles.

◆ topicModellingDefaultOptimizeEvery

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultOptimizeEvery {10}

inline

The default optimization interval for the model parameters, in training iterations.

◆ topicModellingDefaultRemoveTopN

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDefaultRemoveTopN {0}

inline

The default number of most-common tokens to ignore.

◆ topicModellingDirectory

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingDirectory {"mdl"sv}

inline

The directory for model files.

Referenced by crawlservpp::Module::Analyzer::Algo::TopicModelling::resetAlgo().

◆ topicModellingPrecisionLL

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingPrecisionLL {6}

inline

The number of digits of the log-likelihood to be logged.

Referenced by crawlservpp::Module::Analyzer::Algo::TopicModelling::resetAlgo().

◆ topicModellingPrecisionUlp

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingPrecisionUlp {5}

inline

Precision used when testing topic probabilities for equality, in ULPs (units in the last place).

Referenced by crawlservpp::Module::Analyzer::Algo::TopicModelling::resetAlgo().

◆ topicModellingTargetColumns

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingTargetColumns {2}

inline

The number of additional columns in the target table.

Referenced by crawlservpp::Module::Analyzer::Algo::TopicModelling::resetAlgo().

◆ topicModellingTopicColumns

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingTopicColumns {2}

inline

The number of additional columns in the topic table.

Referenced by crawlservpp::Module::Analyzer::Algo::TopicModelling::resetAlgo().

◆ topicModellingUpdateProgressEvery

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingUpdateProgressEvery {1000}

inline

The number of added/saved articles after which the progress will be updated.

Referenced by crawlservpp::Module::Analyzer::Algo::TopicModelling::resetAlgo().

◆ topicModellingUpdateProgressEveryDocs

constexpr auto crawlservpp::Module::Analyzer::Algo::topicModellingUpdateProgressEveryDocs {25}

inline

The number of classified documents after which the progress will be updated.

Referenced by crawlservpp::Module::Analyzer::Algo::TopicModelling::resetAlgo().

◆ wordsNumberOfColumns

constexpr auto crawlservpp::Module::Analyzer::Algo::wordsNumberOfColumns {4}

inline

The number of columns to write to the target table.

Referenced by crawlservpp::Module::Analyzer::Algo::WordsOverTime::onAlgoInitTarget(), and crawlservpp::Module::Analyzer::Algo::WordsOverTime::resetAlgo().

◆ wordsUpdateProgressEvery

constexpr auto crawlservpp::Module::Analyzer::Algo::wordsUpdateProgressEvery {100}

inline

Indicates after how many date groups the progress of the thread will be updated.

Referenced by crawlservpp::Module::Analyzer::Algo::WordsOverTime::resetAlgo().

Classes

Typedefs

Registration

Constants

Detailed Description

Typedef Documentation

◆ AlgoThreadProperties

◆ AlgoThreadPtr

Function Documentation

◆ initAlgo()

Variable Documentation

◆ allTokensColumns

◆ allTokensUpdateEveryArticle

◆ allTokensUpdateEveryDate

◆ allTokensUpdateEveryRow

◆ allTokensUpdateEveryToken

◆ assocAddColumns

◆ assocMinColumns

◆ assocOverTimeAddColumns

◆ assocOverTimeMinColumns

◆ assocOverTimeUpdateProgressEvery

◆ assocUpdateProgressEvery

◆ corpusNumFields

◆ extractIdsUpdateProgressEvery

◆ sentimentArticleColumnsPerCategory

◆ sentimentDefaultThreshold

◆ sentimentDictionary

◆ sentimentEmojis

◆ sentimentMinColumnsPerCategory

◆ sentimentMinNumColumns

◆ sentimentPercentageFactor

◆ sentimentUpdateCalculateProgressEvery

◆ sentimentUpdateSavingProgressEvery

◆ topicModellingColumnsPerLabel

◆ topicModellingColumnsPerToken

◆ topicModellingDefaultAlpha

◆ topicModellingDefaultBurnIn

◆ topicModellingDefaultConversionThreshold

◆ topicModellingDefaultDocIterations

◆ topicModellingDefaultEta

◆ topicModellingDefaultGamma

◆ topicModellingDefaultIterations

◆ topicModellingDefaultIterationsAtOnce

◆ topicModellingDefaultLabelMu

◆ topicModellingDefaultLabelSmoothing

◆ topicModellingDefaultMaxLabelCandidates

◆ topicModellingDefaultMaxLabelLength

◆ topicModellingDefaultMinCf

◆ topicModellingDefaultMinDf

◆ topicModellingDefaultMinLabelCf

◆ topicModellingDefaultMinLabelDf

◆ topicModellingDefaultMinLabelLength

◆ topicModellingDefaultNumberOfThreads

◆ topicModellingDefaultNumberOfTopics

◆ topicModellingDefaultNumberOfTopicTokens

◆ topicModellingDefaultNumberOfWorkers

◆ topicModellingDefaultOptimizeEvery

◆ topicModellingDefaultRemoveTopN

◆ topicModellingDirectory

◆ topicModellingPrecisionLL

◆ topicModellingPrecisionUlp

◆ topicModellingTargetColumns

◆ topicModellingTopicColumns

◆ topicModellingUpdateProgressEvery

◆ topicModellingUpdateProgressEveryDocs

◆ wordsNumberOfColumns

◆ wordsUpdateProgressEvery