def __init__(self, corpus_size=60000, max_dist=2, freq_weighting='natural', dist_weight=1): #freq_weighting possible values - 'natural', 'none', 'log' self.ft = TextModel() self.tokenizer = transformers.Tokenizer.Tokenizer().fit() self.error_detector = transformers.ErrorDetector.ErrorDetector( self.ft).fit() self.candidate_generator = transformers.TrieCandidateGenerator.\ TrieCandidateGenerator(vocab_size=corpus_size, max_dist=max_dist, model=self.ft).fit() self.context_vectorizer = transformers.ContextVectorizer.ContextVectorizer( self.ft, freq_weighting).fit() self.candidate_vectorizer = transformers.CandidateVectorizer.CandidateVectorizer( self.ft).fit() self.similarity_calculator = transformers.SimilarityCalculator.SimilarityCalculator( ).fit() self.score_calculator = transformers.ScoreCalculator.\ ScoreCalculator(distance_weight=dist_weight).fit()