Uses of Class
tc.TCDocument

Packages that use TCDocument

tc

Uses of TCDocument in tc

Methods in tc with parameters of type TCDocument

TCkNNListElement	TCDocument.getEuclidianDistance(TCDocument documentToClassify, java.util.ArrayList corpusAllTermsOfInterest) The function calculates the euclidian distance between two Document-Weight-Vectors given the vector of all relevant terms in the corpus (corpusAllTermsOfInterest) Can e.g.
TCkNNListElement	TCDocument.getCosineSimilarity(TCDocument documentToClassify, java.util.ArrayList corpusAllTermsOfInterest) (ONLY FOR UNNORMALIZED DOCUMENT VECTORS!!) The function calculates the cosine similarity of two Document-Weight-Vectors given the vector of all relevant terms in the corpus (corpusAllTermsOfInterest) Can e.g.
TCkNNListElement	TCDocument.getCosineSimilarityFast(TCDocument documentToClassify, java.util.ArrayList corpusAllTermsOfInterest) The function calculates the cosine similarity of two Document-Weight-Vectors given the vector of all relevant terms in the corpus (corpusAllTermsOfInterest) Can e.g.
void	TCCorpus.applyKNNToTestDocument(TCDocument documentToClassify, int method) applies the kNN classifier to the given document (out of the test documents!) calculates similarity to all documents in the training set and saves the scores in a list together with the labels the documents belonged to
TCkNNResult	TCCorpus.applyKNNToDocumentFromFile(TCDocument documentToClassify, int method, int k) applies the kNN classifier to the given document (loaded from a file before!).
TCkNNResult	TCCorpus.getKNNResultForTestDocument(TCDocument documentToClassify, int k) returns the kNN result, given the test document index and k for the k nearest neighbors classifier
void	TCCorpus.applyNaiveBayesBernoulliToTestDocument(TCDocument documentToClassify) Classifies one document out of the test documents with the naive bayes algorithm (bernoulli).
TCNaiveBayesResult	TCCorpus.applyNaiveBayesBernoulliToDocumentFromFile(TCDocument documentToClassify) Classifies one document out of the test documents with the naive bayes algorithm (bernoulli).
TCNaiveBayesResult	TCCorpus.getNaiveBayesResultForTestDocument(TCDocument documentToClassify) gets the naive bayes classification result for the test document with the given index
void	TCCorpus.addDocument(TCDocument newDocument) adds a new document to the corpus.
double	TCCategory.computeNaiveBayesBernoulli(java.util.ArrayList corpusAllTermsOfInterest, TCDocument documentToClassify) computes the naive bayes (bernoulli) value for this category given all the terms of interest in the entire corpus and the document to classify by the naive bayes agorithm
void	TCCategory.addDocument(TCDocument newDocument) adds a new document to the category