質問編集履歴
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不要箇所削除
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このデータ分割後に次のエラーとなります。
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ValueError Traceback (most recent call last)
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4 from sklearn.model_selection import train_test_split
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----> 5 X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2,stratify=binned_y)
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----> 5 X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2,stratify=binned_y)
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1657 class_counts = np.bincount(y_indices)
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1658 if np.min(class_counts) < 2:
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-> 1659 raise ValueError("The least populated class in y has only 1"
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エラーメッセージの追加
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```
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このデータ分割後に次のエラーとなります。
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---------------------------------------------------------------------------
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ValueError Traceback (most recent call last)
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<ipython-input-35-243282289f03> in <module>()
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4 from sklearn.model_selection import train_test_split
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----> 5 X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2,stratify=binned_y)
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/usr/local/lib/python3.6/dist-packages/sklearn/model_selection/_split.py in _iter_indices(self, X, y, groups)
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1657 class_counts = np.bincount(y_indices)
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1658 if np.min(class_counts) < 2:
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-> 1659 raise ValueError("The least populated class in y has only 1"
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1660 " member, which is too few. The minimum"
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1661 " number of groups for any class cannot"
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ValueError: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
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（上記のエラーの翻訳では、ValueError：yで最も人口の少ないクラスにはメンバーが1つしかなく、少なすぎます。クラスのグループの最小数は2未満にはできません。）
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1
コードの記入方法
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勾配部―スティング決定木のチューニングというアンサンブル学習で回帰予測を
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実施しました。
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```ここに言語を入力
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#Numpyの配列に変換
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y = np.array(dataset[target_col])#ターゲット変数
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X = np.array(dataset[feature_cols])#説明変数
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from sklearn.model_selection import train_test_split
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X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2,stratify=binned_y)
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```
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このデータ分割後に次のエラーとなります。
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ValueError: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.
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