Invert MinMaxScaler from scikit_learn

前端 未结 3 1364
青春惊慌失措
青春惊慌失措 2021-02-20 06:15

To feed my generative neural net, I need to normalize some data between -1 and 1.

I do it with MinMaxScaler from Sklearn and it works great. Now, my generat

相关标签:
3条回答
  • 2021-02-20 06:57
    def rev_min_max_func(scaled_val):
        max_val = max(df['target'])
        min_val = min(df['target'])
        og_val = (scaled_val*(max_val - min_val)) + min_val
        return og_val
    df['pred_target'] = scaled_labeled_df['pred_scaled_target'].apply(lambda x: rev_min_max_func(x))
    

    Even this works for me!

    0 讨论(0)
  • 2021-02-20 07:12

    Let us start by defining a pandas dataframe:

    cols = ['A', 'B']
    data = pd.DataFrame(np.array([[2,3],[1.02,1.2],[0.5,0.3]]),columns=cols)
    

    The we scale the data using the MinMaxScaler

    scaler = preprocessing.MinMaxScaler(feature_range = (0,1))
    scaled_data = scaler.fit_transform(data[cols])
    

    Now, to invert the transformation you should call the inverse transform:

    scaler.inverse_transform(scaled_data)
    

    0 讨论(0)
  • 2021-02-20 07:20

    You do that with inverse transform.

    0 讨论(0)
提交回复
热议问题