Pythonで学ぶ予測分析入門
Nele Verbiest, Ph.D
Data Scientist @PythonPredictions
auc_values = [] variables_evaluate = [] for v in variables_forward: variables_evaluate.append(v) auc_value = auc(variables_evaluate, ["target"], basetable) auc_values.append(auc_value)
from sklearn.model_selection import train_test_split X = basetable.drop("target", 1) y = basetable["target"] X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, stratify = Y) train = pd.concat([X_train, y_train], axis=1) test = pd.concat([X_test, y_test], axis=1)
from sklearn.model_selection import train_test_split
X = basetable.drop("target", 1) y = basetable["target"]
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, stratify = Y)
train = pd.concat([X_train, y_train], axis=1) test = pd.concat([X_test, y_test], axis=1)
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