A B C D E G I L M N O P Q R S T W X

A

AbstractParser - Class in ws.palladian.extraction

This is the AbstractParser.

AbstractParser() - Constructor for class ws.palladian.extraction.AbstractParser

apply(svm_parameter) - Method in interface ws.palladian.classification.LibSvmKernel

apply(svm_parameter) - Method in class ws.palladian.classification.LinearKernel

apply(svm_parameter) - Method in class ws.palladian.classification.RBFKernel

B

BoilerpipeContentExtractor - Class in ws.palladian.extraction.content

Boilerpipe, as described in "Boilerplate Detection using Shallow Text Features"; Kohlschütter, Christian; Fankhauser, Peter; Nejdl, Wolfgang; 2010.

BoilerpipeContentExtractor() - Constructor for class ws.palladian.extraction.content.BoilerpipeContentExtractor

BoilerpipeContentExtractor(ExtractorBase) - Constructor for class ws.palladian.extraction.content.BoilerpipeContentExtractor

build(M, Classifier<M>, Dataset) - Static method in class ws.palladian.classification.utils.ProbabilityCalibratedClassifier

C

categoricalBranch(DTCatBranch, boolean) - Method in class ws.palladian.classification.quickml.ModelStats

categoricalBranch(DTCatBranch, boolean) - Method in interface ws.palladian.classification.quickml.TreeVisitor

chunk(String) - Method in class ws.palladian.extraction.phrase.LingPipePhraseChunker

chunk(String) - Method in class ws.palladian.extraction.phrase.OpenNlpPhraseChunker

classify(FeatureVector, LibLinearModel) - Method in class ws.palladian.classification.liblinear.LibLinearClassifier

classify(FeatureVector, LibSvmModel) - Method in class ws.palladian.classification.LibSvmClassifier

classify(FeatureVector, QuickMlModel) - Method in class ws.palladian.classification.quickml.QuickMlClassifier

classify(FeatureVector, LingPipeTextClassifier.LingPipeTextClassifierModel) - Method in class ws.palladian.classification.text.LingPipeTextClassifier

classify(FeatureVector, NbSvmModel) - Method in class ws.palladian.classification.text.nbsvm.NbSvmClassifier

classify(FeatureVector, OpenNlpTextClassifier.OpenNlpTextClassifierModel) - Method in class ws.palladian.classification.text.OpenNlpTextClassifier

classify(FeatureVector, TextVectorClassifier.TextVectorModel<M>) - Method in class ws.palladian.classification.text.vector.TextVectorClassifier

classify(FeatureVector, M) - Method in class ws.palladian.classification.utils.ProbabilityCalibratedClassifier

classify(FeatureVector, WekaModel) - Method in class ws.palladian.classification.WekaClassifier

classify(FeatureVector, XGBoostModel) - Method in class ws.palladian.classification.xgboost.XGBoostClassifier

ClavinLocationExtractor - Class in ws.palladian.extraction.location

Wrapper for CLAVIN (Cartographic Location And Vicinity INdexer) by Berico Technologies.

ClavinLocationExtractor(String) - Constructor for class ws.palladian.extraction.location.ClavinLocationExtractor

Create a new ClavinLocationExtractor.

ContentExtractionEvaluationRunner - Class in ws.palladian.extraction.content.evaluation

ContentExtractionEvaluationRunner() - Constructor for class ws.palladian.extraction.content.evaluation.ContentExtractionEvaluationRunner

D

DEFAULT_TRAINING_ROUNDS - Static variable in class ws.palladian.extraction.entity.tagger.IllinoisNer

The default number of training rounds.

E

eval(float[][], DMatrix) - Method in class ws.palladian.classification.xgboost.MCCEvaluation

Deprecated.

eval(float[][], DMatrix) - Method in class ws.palladian.classification.xgboost.MCCEvaluation2

evaluate(String, String) - Method in class ws.palladian.extraction.pos.LingPipePosTagger

G

getAnnotations(String) - Method in class ws.palladian.extraction.entity.tagger.IllinoisNer

getAnnotations(String) - Method in class ws.palladian.extraction.entity.tagger.LingPipeNer

getAnnotations(String) - Method in class ws.palladian.extraction.entity.tagger.OpenNlpNer

getAnnotations(String) - Method in class ws.palladian.extraction.entity.tagger.StanfordNer

getAnnotations(String) - Method in class ws.palladian.extraction.location.ClavinLocationExtractor

getCategories() - Method in class ws.palladian.classification.liblinear.LibLinearModel

getCategories() - Method in class ws.palladian.classification.LibSvmModel

getCategories() - Method in class ws.palladian.classification.quickml.QuickMlModel

getCategories() - Method in class ws.palladian.classification.text.LingPipeTextClassifier.LingPipeTextClassifierModel

getCategories() - Method in class ws.palladian.classification.text.nbsvm.NbSvmModel

getCategories() - Method in class ws.palladian.classification.text.OpenNlpTextClassifier.OpenNlpTextClassifierModel

getCategories() - Method in class ws.palladian.classification.text.vector.TextVectorClassifier.TextVectorModel

getCategories() - Method in class ws.palladian.classification.WekaModel

getCategories() - Method in class ws.palladian.classification.xgboost.XGBoostModel

getClassifier() - Method in class ws.palladian.classification.quickml.QuickMlModel

getClassifier() - Method in class ws.palladian.classification.WekaModel

getDataset() - Method in class ws.palladian.classification.WekaModel

getDummyCoder() - Method in class ws.palladian.classification.LibSvmModel

getExtractorName() - Method in class ws.palladian.extraction.content.BoilerpipeContentExtractor

getExtractorName() - Method in class ws.palladian.extraction.content.GooseContentExtractor

getFeatureGenerator() - Method in class ws.palladian.classification.text.OpenNlpTextClassifier.OpenNlpTextClassifierModel

getFeatureRanking() - Method in class ws.palladian.classification.quickml.ModelStats

getFeatureRanking() - Method in class ws.palladian.classification.xgboost.XGBoostModel

getFeatureScore() - Method in class ws.palladian.classification.xgboost.XGBoostModel

Deprecated.

Use XGBoostModel.getFeatureRanking() instead.

getFullParse(String) - Method in class ws.palladian.extraction.OpenNlpParser

Returns the full parse for a sentence as openNLP parse.

getMetric() - Method in class ws.palladian.classification.xgboost.MCCEvaluation

Deprecated.

getMetric() - Method in class ws.palladian.classification.xgboost.MCCEvaluation2

getModel() - Method in class ws.palladian.classification.LibSvmModel

getModel() - Method in class ws.palladian.extraction.AbstractParser

getModelFileEnding() - Method in class ws.palladian.extraction.entity.tagger.IllinoisNer

getModelFileEnding() - Method in class ws.palladian.extraction.entity.tagger.LingPipeNer

getModelFileEnding() - Method in class ws.palladian.extraction.entity.tagger.OpenNlpNer

getModelFileEnding() - Method in class ws.palladian.extraction.entity.tagger.StanfordNer

getName() - Method in class ws.palladian.extraction.AbstractParser

getName() - Method in class ws.palladian.extraction.entity.tagger.IllinoisNer

getName() - Method in class ws.palladian.extraction.entity.tagger.LingPipeNer

getName() - Method in class ws.palladian.extraction.entity.tagger.OpenNlpNer

getName() - Method in class ws.palladian.extraction.entity.tagger.StanfordNer

getName() - Method in class ws.palladian.extraction.location.ClavinLocationExtractor

getName() - Method in class ws.palladian.extraction.phrase.LingPipePhraseChunker

getName() - Method in class ws.palladian.extraction.phrase.OpenNlpPhraseChunker

getName() - Method in class ws.palladian.extraction.pos.LingPipePosTagger

getName() - Method in class ws.palladian.extraction.pos.OpenNlpPosTagger

getNormalization() - Method in class ws.palladian.classification.LibSvmModel

getParse() - Method in class ws.palladian.extraction.OpenNlpParser

getResultNode() - Method in class ws.palladian.extraction.content.BoilerpipeContentExtractor

getResultNode() - Method in class ws.palladian.extraction.content.GooseContentExtractor

getResultText() - Method in class ws.palladian.extraction.content.BoilerpipeContentExtractor

getResultText() - Method in class ws.palladian.extraction.content.GooseContentExtractor

getResultTitle() - Method in class ws.palladian.extraction.content.BoilerpipeContentExtractor

getResultTitle() - Method in class ws.palladian.extraction.content.GooseContentExtractor

getSchema() - Method in class ws.palladian.classification.LibSvmModel

getSchema() - Method in class ws.palladian.classification.WekaModel

getTagAnnotations() - Method in class ws.palladian.extraction.AbstractParser

getTags(List<String>) - Method in class ws.palladian.extraction.pos.LingPipePosTagger

getTags(List<String>) - Method in class ws.palladian.extraction.pos.OpenNlpPosTagger

getTokenizer() - Method in class ws.palladian.extraction.pos.LingPipePosTagger

GooseContentExtractor - Class in ws.palladian.extraction.content

Content extractor using Goose.

GooseContentExtractor() - Constructor for class ws.palladian.extraction.content.GooseContentExtractor

I

IllinoisNer - Class in ws.palladian.extraction.entity.tagger

This class wraps the Learning Java Based Illinois Named Entity Tagger.

IllinoisNer(int) - Constructor for class ws.palladian.extraction.entity.tagger.IllinoisNer

Create a new IllinoisNer using specified number of iterations for training.

IllinoisNer() - Constructor for class ws.palladian.extraction.entity.tagger.IllinoisNer

Create a new IllinoisNer using the automatic convergence criterion for training.

iterateTokens(String) - Method in class ws.palladian.extraction.sentence.LingPipeSentenceDetector

iterateTokens(String) - Method in class ws.palladian.extraction.sentence.OpenNlpSentenceDetector

iterateTokens(String) - Method in class ws.palladian.extraction.token.LingPipeTokenizer

iterateTokens(String) - Method in class ws.palladian.extraction.token.OpenNlpTokenizer

iterateTokens(String) - Method in class ws.palladian.extraction.token.TwokenizeTokenizer

L

leaf(DTLeaf, boolean) - Method in class ws.palladian.classification.quickml.ModelStats

leaf(DTLeaf, boolean) - Method in interface ws.palladian.classification.quickml.TreeVisitor

libLinear(ITextVectorizer) - Static method in class ws.palladian.classification.text.vector.TextVectorClassifier

libLinear(ITextVectorizer, Parameter) - Static method in class ws.palladian.classification.text.vector.TextVectorClassifier

LibLinearClassifier - Class in ws.palladian.classification.liblinear

Classifier for models created via LibLinearLearner.

LibLinearClassifier() - Constructor for class ws.palladian.classification.liblinear.LibLinearClassifier

LibLinearLearner - Class in ws.palladian.classification.liblinear

LIBLINEAR, A Library for Large Linear Classification.

LibLinearLearner(Parameter, double, Normalizer) - Constructor for class ws.palladian.classification.liblinear.LibLinearLearner

Create a new LibLinearLearner with the specified Parameter for training.

LibLinearLearner(Normalizer) - Constructor for class ws.palladian.classification.liblinear.LibLinearLearner

Create a new LibLinearLearner with 'L2-regularized logistic regression', a cost value of 1.0 for constraints violation, a value of 0.01 as stopping criterion, and a bias term of one

LibLinearLearner() - Constructor for class ws.palladian.classification.liblinear.LibLinearLearner

Create a new LibLinearLearner with 'L2-regularized logistic regression', a cost value of 1.0 for constraints violation, a value of 0.01 as stopping criterion, a bias term of one, and Z-Score normalization for features.

LibLinearModel - Class in ws.palladian.classification.liblinear

Model for the LibLinearClassifier.

LibSvmClassifier - Class in ws.palladian.classification

A wrapper classifier for the LIBSVM machine learning library.

LibSvmClassifier() - Constructor for class ws.palladian.classification.LibSvmClassifier

LibSvmKernel - Interface in ws.palladian.classification

Implemented by all kernels available for the LibSvmPredictor.

LibSvmLearner - Class in ws.palladian.classification

A wrapper classifier for the LIBSVM machine learning library.

LibSvmLearner(LibSvmKernel) - Constructor for class ws.palladian.classification.LibSvmLearner

Creates a new completely initialized LibSvmLearner using a linear kernel.

LibSvmModel - Class in ws.palladian.classification

LinearKernel - Class in ws.palladian.classification

An SVM kernel using a linear base function.

LinearKernel(double) - Constructor for class ws.palladian.classification.LinearKernel

LingPipeNer - Class in ws.palladian.extraction.entity.tagger

This class wraps the LingPipe implementation of a Named Entity Recognizer.

LingPipeNer() - Constructor for class ws.palladian.extraction.entity.tagger.LingPipeNer

LingPipePhraseChunker - Class in ws.palladian.extraction.phrase

Expects to chunk 1 sentence at a time.

LingPipePhraseChunker(File) - Constructor for class ws.palladian.extraction.phrase.LingPipePhraseChunker

constructor

LingPipePosTagger - Class in ws.palladian.extraction.pos

POS tagger based on LingPipe.

LingPipePosTagger(File) - Constructor for class ws.palladian.extraction.pos.LingPipePosTagger

Creates a new completely initalized LingPipe PoS tagger from the given model using the provided TagFilter .

LingPipePosTagger(InputStream) - Constructor for class ws.palladian.extraction.pos.LingPipePosTagger

LingPipeSentenceDetector - Class in ws.palladian.extraction.sentence

A sentence detector based on the implementation provided by the Lingpipe framework.

LingPipeSentenceDetector() - Constructor for class ws.palladian.extraction.sentence.LingPipeSentenceDetector

Create a new LingPipeSentenceDetector.

LingPipeTextClassifier - Class in ws.palladian.classification.text

LingPipeTextClassifier(FeatureExtractor<CharSequence>) - Constructor for class ws.palladian.classification.text.LingPipeTextClassifier

LingPipeTextClassifier.LingPipeTextClassifierModel - Class in ws.palladian.classification.text

LingPipeTokenizer - Class in ws.palladian.extraction.token

A AbstractTokenizer implementation based on LingPipe's IndoEuropeanTokenizerFactory.

LingPipeTokenizer() - Constructor for class ws.palladian.extraction.token.LingPipeTokenizer

link(Parse[]) - Method in class ws.palladian.extraction.OpenNlpParser

Identifies coreferences in an array of full parses of sentences.

loadDefaultModel() - Method in class ws.palladian.extraction.AbstractParser

loads the default model into the parser.

loadDefaultModel() - Method in class ws.palladian.extraction.OpenNlpParser

loadModel(String) - Method in class ws.palladian.extraction.AbstractParser

loads the model into the parser.

loadModel(String) - Method in class ws.palladian.extraction.entity.tagger.IllinoisNer

loadModel(String) - Method in class ws.palladian.extraction.entity.tagger.LingPipeNer

loadModel(String) - Method in class ws.palladian.extraction.entity.tagger.OpenNlpNer

Load the models for the entity recognizer.

loadModel(String) - Method in class ws.palladian.extraction.entity.tagger.StanfordNer

loadModel(String) - Method in class ws.palladian.extraction.OpenNlpParser

LOGGER - Static variable in class ws.palladian.extraction.AbstractParser

Logger for this class.

LOGGER - Static variable in class ws.palladian.extraction.OpenNlpParser

Logger for this class.

M

main(String[]) - Static method in class ws.palladian.classification.xgboost.XGBoostModel

main(String[]) - Static method in class ws.palladian.extraction.content.evaluation.ContentExtractionEvaluationRunner

main(String[]) - Static method in class ws.palladian.extraction.content.GooseContentExtractor

main(String[]) - Static method in class ws.palladian.extraction.entity.tagger.LingPipeNer

main(String[]) - Static method in class ws.palladian.extraction.entity.tagger.StanfordNer

main(String[]) - Static method in class ws.palladian.extraction.location.ClavinLocationExtractor

main(String[]) - Static method in class ws.palladian.extraction.pos.LingPipePosTagger

MCCEvaluation - Class in ws.palladian.classification.xgboost

Deprecated.

This one uses a fixed threshold of 0.5, however there might be a better threshold which gives a higher MCC. Use MCCEvaluation2 instead.

MCCEvaluation() - Constructor for class ws.palladian.classification.xgboost.MCCEvaluation

Deprecated.

MCCEvaluation2 - Class in ws.palladian.classification.xgboost

Evaluation function for Matthews Correlation Coefficient.

MCCEvaluation2() - Constructor for class ws.palladian.classification.xgboost.MCCEvaluation2

ModelStats - Class in ws.palladian.classification.quickml

ModelStats() - Constructor for class ws.palladian.classification.quickml.ModelStats

N

NbSvmClassifier - Class in ws.palladian.classification.text.nbsvm

Classifier for the NBSVM (SVM with NB features) text classifier described in "Baselines and Bigrams: Simple, Good Sentiment and Topic Classification"; Sida Wang and Christopher D.

NbSvmClassifier(TextVectorizer) - Constructor for class ws.palladian.classification.text.nbsvm.NbSvmClassifier

NbSvmLearner - Class in ws.palladian.classification.text.nbsvm

Learner for the NBSVM (SVM with NB features) text classifier described in "Baselines and Bigrams: Simple, Good Sentiment and Topic Classification"; Sida Wang and Christopher D.

NbSvmLearner(TextVectorizer) - Constructor for class ws.palladian.classification.text.nbsvm.NbSvmLearner

NbSvmLearner(TextVectorizer, Parameter) - Constructor for class ws.palladian.classification.text.nbsvm.NbSvmLearner

NbSvmModel - Class in ws.palladian.classification.text.nbsvm

numericalBranch(DTNumBranch, boolean) - Method in class ws.palladian.classification.quickml.ModelStats

numericalBranch(DTNumBranch, boolean) - Method in interface ws.palladian.classification.quickml.TreeVisitor

O

oneModelPerConcept() - Method in class ws.palladian.extraction.entity.tagger.OpenNlpNer

OpenNlpNer - Class in ws.palladian.extraction.entity.tagger

This class wraps the OpenNLP Named Entity Recognizer which uses a maximum entropy approach.

OpenNlpNer(Tokenizer, SentenceDetector) - Constructor for class ws.palladian.extraction.entity.tagger.OpenNlpNer

Create a new OpenNlpNer.

OpenNlpParser - Class in ws.palladian.extraction

OpenNLP Parser

OpenNlpParser(File, File) - Constructor for class ws.palladian.extraction.OpenNlpParser

OpenNlpPhraseChunker - Class in ws.palladian.extraction.phrase

OpenNlpPhraseChunker(File, File) - Constructor for class ws.palladian.extraction.phrase.OpenNlpPhraseChunker

OpenNlpPosTagger - Class in ws.palladian.extraction.pos

Apache OpenNLP based POS tagger.

OpenNlpPosTagger(File) - Constructor for class ws.palladian.extraction.pos.OpenNlpPosTagger

OpenNlpSentenceDetector - Class in ws.palladian.extraction.sentence

A sentence detector using an implementation from the OpenNLP framework.

OpenNlpSentenceDetector(File) - Constructor for class ws.palladian.extraction.sentence.OpenNlpSentenceDetector

Creates a new completely initialized sentence detector.

OpenNlpTextClassifier - Class in ws.palladian.classification.text

Text classifier which uses Open NLP's DocumentCategorizerME.

OpenNlpTextClassifier(Language, FeatureGenerator) - Constructor for class ws.palladian.classification.text.OpenNlpTextClassifier

OpenNlpTextClassifier.OpenNlpTextClassifierModel - Class in ws.palladian.classification.text

OpenNlpTokenizer - Class in ws.palladian.extraction.token

A TextTokenizer implemenation based on Apache OpenNLP.

OpenNlpTokenizer() - Constructor for class ws.palladian.extraction.token.OpenNlpTokenizer

Create a new OpenNlpTokenizer using a SimpleTokenizer, which tokenizes based on same character classes.

OpenNlpTokenizer(Tokenizer) - Constructor for class ws.palladian.extraction.token.OpenNlpTokenizer

Create a new OpenNlpTokenizer using an arbitrary implementation of Tokenizer.

OpenNlpTokenizer(File) - Constructor for class ws.palladian.extraction.token.OpenNlpTokenizer

Create a new OpenNlpTokenizer based on a learned model.

P

parse(String) - Method in class ws.palladian.extraction.AbstractParser

Parses a given string and writes it into the parse object of this class.

parse(String) - Method in class ws.palladian.extraction.OpenNlpParser

Peforms a full parsing on a sentence of space-delimited tokens.

parse(String, int) - Method in class ws.palladian.extraction.OpenNlpParser

Persforms a full parse and selects the given index where 0 is the most likely parse

parse2Annotations(Parse, List<Annotation>) - Method in class ws.palladian.extraction.AbstractParser

Converts a parse tree into Annotations.

printParse(Parse) - Method in class ws.palladian.extraction.AbstractParser

Prints out the parse tree.

ProbabilityCalibratedClassifier<M extends Model> - Class in ws.palladian.classification.utils

Q

QuickMlClassifier - Class in ws.palladian.classification.quickml

Classifier for models built with QuickMlLearner.

QuickMlClassifier() - Constructor for class ws.palladian.classification.quickml.QuickMlClassifier

QuickMlLearner - Class in ws.palladian.classification.quickml

A classifier based on QuickML by Ian Clarke.

QuickMlLearner(PredictiveModelBuilder<? extends Classifier, ClassifierInstance>) - Constructor for class ws.palladian.classification.quickml.QuickMlLearner

Create a new QuickMlLearner with the specified PredictiveModelBuilder.

QuickMlModel - Class in ws.palladian.classification.quickml

Wrapper for QuickML's predictive models.

R

randomForest() - Static method in class ws.palladian.classification.quickml.QuickMlLearner

randomForest(int) - Static method in class ws.palladian.classification.quickml.QuickMlLearner

RBFKernel - Class in ws.palladian.classification

A LibSvm kernel using a gaussian basis function.

RBFKernel(double, double) - Constructor for class ws.palladian.classification.RBFKernel

S

SelfTuningLibLinearLearner - Class in ws.palladian.classification.liblinear

Performs a tuning on the penalty parameter C for the LibLinearLearner by applying a k-fold cross validation, as suggested in "A Practical Guide to Support Vector Classification", Chih-Wei Hsu, Chih-Chung Chang, and Chih-Jen Lin, 2010.

SelfTuningLibLinearLearner(int) - Constructor for class ws.palladian.classification.liblinear.SelfTuningLibLinearLearner

SelfTuningLibSvmLearner - Class in ws.palladian.classification

Performs a tuning on the penalty parameter C and gamma for the LibSvmLearner by applying a k-fold cross validation, as suggested in "A Practical Guide to Support Vector Classification", Chih-Wei Hsu, Chih-Chung Chang, and Chih-Jen Lin, 2010.

SelfTuningLibSvmLearner(int) - Constructor for class ws.palladian.classification.SelfTuningLibSvmLearner

setDocument(File) - Method in class ws.palladian.extraction.content.BoilerpipeContentExtractor

setDocument(Document) - Method in class ws.palladian.extraction.content.BoilerpipeContentExtractor

setDocument(InputSource) - Method in class ws.palladian.extraction.content.BoilerpipeContentExtractor

setDocument(File) - Method in class ws.palladian.extraction.content.GooseContentExtractor

setDocument(HttpResult) - Method in class ws.palladian.extraction.content.GooseContentExtractor

setDocument(String) - Method in class ws.palladian.extraction.content.GooseContentExtractor

setDocument(URL) - Method in class ws.palladian.extraction.content.GooseContentExtractor

setDocument(Document) - Method in class ws.palladian.extraction.content.GooseContentExtractor

setModel(Object) - Method in class ws.palladian.extraction.AbstractParser

setName(String) - Method in class ws.palladian.extraction.AbstractParser

setParse(Parse) - Method in class ws.palladian.extraction.OpenNlpParser

setsModelFileEndingAutomatically() - Method in class ws.palladian.extraction.entity.tagger.IllinoisNer

setsModelFileEndingAutomatically() - Method in class ws.palladian.extraction.entity.tagger.LingPipeNer

setsModelFileEndingAutomatically() - Method in class ws.palladian.extraction.entity.tagger.OpenNlpNer

setsModelFileEndingAutomatically() - Method in class ws.palladian.extraction.entity.tagger.StanfordNer

setTagAnnotations(List<Annotation>) - Method in class ws.palladian.extraction.AbstractParser

StanfordNer - Class in ws.palladian.extraction.entity.tagger

This class wraps the Stanford Named Entity Recognizer which is based on conditional random fields (CRF).

StanfordNer() - Constructor for class ws.palladian.extraction.entity.tagger.StanfordNer

T

TextVectorClassifier<M extends Model> - Class in ws.palladian.classification.text.vector

TextVectorClassifier(ITextVectorizer, Learner<M>, Classifier<M>) - Constructor for class ws.palladian.classification.text.vector.TextVectorClassifier

TextVectorClassifier.TextVectorModel<M extends Model> - Class in ws.palladian.classification.text.vector

TextVectorModel(M) - Constructor for class ws.palladian.classification.text.vector.TextVectorClassifier.TextVectorModel

toString() - Method in class ws.palladian.classification.liblinear.LibLinearLearner

toString() - Method in class ws.palladian.classification.liblinear.LibLinearModel

toString() - Method in class ws.palladian.classification.LibSvmLearner

toString() - Method in class ws.palladian.classification.quickml.ModelStats

toString() - Method in class ws.palladian.classification.quickml.QuickMlLearner

toString() - Method in class ws.palladian.classification.quickml.QuickMlModel

toString() - Method in class ws.palladian.classification.text.nbsvm.NbSvmLearner

toString() - Method in class ws.palladian.classification.text.vector.TextVectorClassifier

toString() - Method in class ws.palladian.classification.WekaLearner

toString() - Method in class ws.palladian.classification.xgboost.XGBoostModel

train(Dataset) - Method in class ws.palladian.classification.liblinear.LibLinearLearner

train(Dataset) - Method in class ws.palladian.classification.liblinear.SelfTuningLibLinearLearner

train(Dataset) - Method in class ws.palladian.classification.LibSvmLearner

train(Dataset) - Method in class ws.palladian.classification.quickml.QuickMlLearner

train(Dataset) - Method in class ws.palladian.classification.SelfTuningLibSvmLearner

train(Dataset) - Method in class ws.palladian.classification.text.LingPipeTextClassifier

train(Dataset) - Method in class ws.palladian.classification.text.nbsvm.NbSvmLearner

train(Dataset) - Method in class ws.palladian.classification.text.OpenNlpTextClassifier

train(Dataset) - Method in class ws.palladian.classification.text.vector.TextVectorClassifier

train(Dataset) - Method in class ws.palladian.classification.WekaLearner

train(Dataset, Dataset) - Method in class ws.palladian.classification.xgboost.XGBoostLearner

train(Dataset) - Method in class ws.palladian.classification.xgboost.XGBoostLearner

train(String, String) - Method in class ws.palladian.extraction.entity.tagger.IllinoisNer

train(String, String) - Method in class ws.palladian.extraction.entity.tagger.LingPipeNer

train(String, String) - Method in class ws.palladian.extraction.entity.tagger.OpenNlpNer

train(String, String) - Method in class ws.palladian.extraction.entity.tagger.StanfordNer

transformClassToString(int) - Method in class ws.palladian.classification.LibSvmModel

traverseModel(TV) - Method in class ws.palladian.classification.quickml.QuickMlModel

Allows to traverse the model using a visitor.

tree(DecisionTree) - Method in class ws.palladian.classification.quickml.ModelStats

tree() - Static method in class ws.palladian.classification.quickml.QuickMlLearner

tree(DecisionTree) - Method in interface ws.palladian.classification.quickml.TreeVisitor

TreeVisitor - Interface in ws.palladian.classification.quickml

Visitor for decision tree and random forest models.

TwokenizeTokenizer - Class in ws.palladian.extraction.token

Tokenizer based on the Twokenize algorithm available from here.

TwokenizeTokenizer() - Constructor for class ws.palladian.extraction.token.TwokenizeTokenizer

W

WekaClassifier - Class in ws.palladian.classification

Classifier wrapper for Weka.

WekaClassifier() - Constructor for class ws.palladian.classification.WekaClassifier

WekaLearner - Class in ws.palladian.classification

Learner wrapper for Weka classifiers.

WekaLearner(Classifier) - Constructor for class ws.palladian.classification.WekaLearner

Create a new WekaLearner with the specified Weka Classifier implementation.

WekaModel - Class in ws.palladian.classification

A Palladian model wrapping a Weka classifier and all information necessary to apply that classifier.

WekaModel(Classifier, Instances) - Constructor for class ws.palladian.classification.WekaModel

ws.palladian.classification - package ws.palladian.classification

ws.palladian.classification.liblinear - package ws.palladian.classification.liblinear

ws.palladian.classification.quickml - package ws.palladian.classification.quickml

ws.palladian.classification.text - package ws.palladian.classification.text

ws.palladian.classification.text.nbsvm - package ws.palladian.classification.text.nbsvm

ws.palladian.classification.text.vector - package ws.palladian.classification.text.vector

ws.palladian.classification.utils - package ws.palladian.classification.utils

ws.palladian.classification.xgboost - package ws.palladian.classification.xgboost

ws.palladian.extraction - package ws.palladian.extraction

ws.palladian.extraction.content - package ws.palladian.extraction.content

ws.palladian.extraction.content.evaluation - package ws.palladian.extraction.content.evaluation

ws.palladian.extraction.entity.tagger - package ws.palladian.extraction.entity.tagger

ws.palladian.extraction.location - package ws.palladian.extraction.location

ws.palladian.extraction.phrase - package ws.palladian.extraction.phrase

ws.palladian.extraction.pos - package ws.palladian.extraction.pos

ws.palladian.extraction.sentence - package ws.palladian.extraction.sentence

ws.palladian.extraction.token - package ws.palladian.extraction.token

X

XGBoostClassifier - Class in ws.palladian.classification.xgboost

XGBoostClassifier() - Constructor for class ws.palladian.classification.xgboost.XGBoostClassifier

XGBoostLearner - Class in ws.palladian.classification.xgboost

Learner for XGBoost: "Scalable and Flexible Gradient Boosting".

XGBoostLearner(Map<String, Object>, int, IEvaluation) - Constructor for class ws.palladian.classification.xgboost.XGBoostLearner

Create a new XGBoostLearner instance with the supplied parameters and a custom evaluation function.

XGBoostLearner(Map<String, Object>, int) - Constructor for class ws.palladian.classification.xgboost.XGBoostLearner

Create a new XGBoostLearner instance with the supplied parameters.

XGBoostLearner() - Constructor for class ws.palladian.classification.xgboost.XGBoostLearner

Create a new XGBoostModel with settings which I took from some Kaggle posts.

XGBoostModel - Class in ws.palladian.classification.xgboost

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