1. 评估函数

  • Classification metrics

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    from sklearn import metrics

    metrics.roc_auc_score(y_true,y_pre)

    # F1 = 2 * (precision * recall) / (precision + recall)
    metrics.f1_score(y_true,y_pre)

  • Regression metrics

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    metrics.mean_absolute_error(y_true,y_pre)
    metrics.mean_squared_error(y_true,y_pre)
  1. 标准化和归一化
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    from sklearn.preprocessing import StandardScaler
    from sklearn.preprocessing import MinMaxScaler

    # 标准化
    ss = StandardScaler() 
    std_data = ss.fit_transform(data) 
    origin_data = ss.inverse_transform(std_data) # 还原

    # 归一化
    mm = MinMaxScaler()
    mm_data = mm.fit_transform(data)
    origin_data = mm.inverse_transform(mm_data)