scikitre.py 文件源码

def __init__(self, corpus, relationtype, modelname="scikit_classifier"):
        super(ScikitRE, self).__init__()
        self.modelname = relationtype + "_" + modelname
        self.relationtype = relationtype
        self.pairtype = relationtype
        self.corpus = corpus
        self.pairs = []
        self.features = []
        self.labels = []
        self.pred = []
        self.clusters = word2vec.load_clusters("corpora/Thaliana/documents-processed-clusters.txt")
        self.posfmeasure = make_scorer(f1_score, average='binary', pos_label=True)
        self.generate_data(corpus, modelname, relationtype)
        self.text_clf = Pipeline([('vect', CountVectorizer(analyzer='char_wb', ngram_range=(3,20), min_df=0.0, max_df=0.7)),
                                  #('vect', CountVectorizer(ngram_range=(1,3), binary=False, max_features=None)),
                                  #('tfidf', TfidfTransformer(use_idf=True, norm="l2")),
                                  #('clf', SGDClassifier(loss='hinge', penalty='l1', alpha=0.0001, n_iter=5, random_state=42)),
                                  #('clf', SGDClassifier())
                                  #('clf', svm.NuSVC(nu=0.01 ))
                                   #('clf', RandomForestClassifier(class_weight={False:1, True:2}, n_jobs=-1))
                                  ('clf', MultinomialNB(alpha=0.01, fit_prior=False))
                                  #('clf', DummyClassifier(strategy="constant", constant=True))
                                 ])