contentView.py 文件源码

 复制代码def fitAndPredict(self):
        # classifier = LogisticRegression()
        # classifier.fit(self.trainingSet, self.trainingLabel)
        # pred_labels = classifier.predict(self.testSet)
        # print 'Logistic:'
        # print classification_report(self.testLabel, pred_labels)

        classifier = SVC()
        classifier.fit(self.trainingSet, self.trainingLabel)
        pred_labels = {}

        for user in self.testDict:
            pred_labels[user] = classifier.predict([self.model.docvecs[user]])
        # print 'SVM:'
        # print classification_report(self.testLabel, pred_labels)
        return pred_labels

        # classifier = GradientBoostingClassifier(n_estimators=100, learning_rate=1.0,
        #                                         max_depth=1, random_state=0)
        # classifier.fit(self.trainingSet, self.trainingLabel)
        # pred_labels = classifier.predict(self.testSet)
        # print 'GBDT:'
        # print classification_report(self.testLabel, pred_labels)
        #
        # clf = AdaBoostClassifier(n_estimators=100)
        # classifier.fit(self.trainingSet, self.trainingLabel)
        # pred_labels = classifier.predict(self.testSet)
        # print 'AdaBoost:'
        # print classification_report(self.testLabel, pred_labels)
        #
        # clf = RandomForestClassifier(n_estimators=10)
        # classifier.fit(self.trainingSet, self.trainingLabel)
        # pred_labels = classifier.predict(self.testSet)
        # print 'Random Forest:'
        # print classification_report(self.testLabel, pred_labels)