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()
