Cross_val_score、Cross_val_score、StratifiedKFold在PTT/mobile01評價與討論，在ptt社群跟網路上大家這樣說
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Cross_val_score在sklearn.model_selection.cross_val_score的討論與評價
sklearn.model_selection .cross_val_score¶ ... Read more in the User Guide. ... A str (see model evaluation documentation) or a scorer callable object / function ...
Cross_val_score在[Day29]機器學習：交叉驗證！ - iT 邦幫忙的討論與評價
from sklearn.cross_validation import cross_val_score ... scores = cross_val_score(knn,X,y,cv=5,scoring='accuracy') print(scores) print(scores.mean()).
Cross_val_score在cross_val_score交叉验证及其用于参数选择、模型选择 - CSDN ...的討論與評價
from sklearn.cross_validation import cross_val_score ... 手动的分割数据 # cv参数用于规定将原始数据分成多少份 scores = cross_val_score(knn, ...
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Cross_val_score在Python cross_validation.cross_val_score方法代碼示例- 純淨天空的討論與評價
需要導入模塊: from sklearn import cross_validation [as 別名] # 或者: from sklearn.cross_validation import cross_val_score [as 別名] def ...
Cross_val_score在sklearn.model_selection.cross_val_score-scikit-learn中文社区的討論與評價
sklearn.model_selection.cross_val_score(estimator, X, y=None, *, groups=None, scoring=None, cv=None, n_jobs=None, verbose=0, fit_params=None, ...
Cross_val_score在在sklearn cross_val_score上評估多個分數- PYTHON _程式人生的討論與評價
如果要返回所有這些值，則必須對 cross_val_score (cross_validation.py的1351行)和 _score (1601行或同一檔案)進行一些更改。 from sklearn.svm import ...
Cross_val_score在python - cross_val_score 和cross_val_predict 的区别 - IT工具网的討論與評價
我想使用交叉验证来评估使用scikitlearn 构建的回归模型并感到困惑，这两个函数中的哪一个 cross_val_score 和 cross_val_predict 我应该用。 一种选择是:
Cross_val_score在pmdarima.model_selection.cross_val_score - alkaline-ml的討論與評價
cross_val_score ¶. pmdarima.model_selection. cross_val_score (estimator, y, X=None, scoring=None, cv=None ...
Cross_val_score在Need help understanding cross_val_score in sklearn python的討論與評價
cross_val_score does the exact same thing in all your examples. It takes the features df and target y , splits into k-folds (which is the cv ...
Cross_val_score在Python sklearn.model_selection 模块，cross_val_score() 实例 ...的討論與評價
StratifiedKFold(n_splits=bcast_var[1], shuffle=False) accuracy = np.mean(model_selection.cross_val_score(clf, data, y=bcast_var[0], cv=skf, ...