Python TfidfVectorizer.score方法代碼示例

本文整理匯總了Python中sklearn.feature_extraction.text.TfidfVectorizer.score方法的典型用法代碼示例。如果您正苦於以下問題：Python TfidfVectorizer.score方法的具體用法？Python TfidfVectorizer.score怎麽用？Python TfidfVectorizer.score使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類sklearn.feature_extraction.text.TfidfVectorizer的用法示例。

在下文中一共展示了TfidfVectorizer.score方法的1個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。

示例1: getScrapedContent

# 需要導入模塊: from sklearn.feature_extraction.text import TfidfVectorizer [as 別名]
# 或者: from sklearn.feature_extraction.text.TfidfVectorizer import score [as 別名]
    content_df = getScrapedContent()
    X, y       = combineHistVolColumn(content_df, sp_df)

    # vectorize text
    clf  = TfidfVectorizer(stop_words='english')
    clfv = clf.fit_transform(X)

    # cross validation
    X_train, X_test, y_train, y_test = train_test_split(clfv, y, test_size=0.2, random_state=42)

    # use naive bayes
    clf = LinearRegression()
    clf.fit(X_train, y_train)
    
    y_pred = clf.predict(X_test)

    ipdb.set_trace()
    # 1 estimator score method
    print "Estimator score method: ", clf.score(X_test, y_test)
    # 2 scoring parameter
    scores = cross_val_score(clf, X_train, y_train, cv=5, scoring='accuracy')

    print "Scoring parameter 'accuracy' from cross val: %0.2f (+/- %0.2f)" % (scores.mean(), scores.std() / 2)

    # 3 scoring via metric functions
    # print average_precision_score(y_test, y_pred)
    print confusion_matrix(y_test, y_pred)

開發者ID:OspreyX，項目名稱:VolatilityPrediction，代碼行數:29，代碼來源:sentimentmodel.py

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