如何将sklearn MinMaxScaler()的值转换回真实值?

use*_*575 0 python scikit-learn keras tensorflow

我这样使用sklearn MinMaxScaler()。

from sklearn.preprocessing import MinMaxScaler

sc = MinMaxScaler()

train_sc = sc.fit_transform(train)
test_sc = sc.transform(test)
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它将数据更改为0-1范围。在我已经预测它仍然是值0-1之后。如何转换回真实价值?

Viv*_*mar 5

用于inverse_transform()输出的预测数据。

from sklearn.preprocessing import MinMaxScaler

data = [[-1, 2], [-0.5, 6], [0, 10], [1, 18]]
scaler = MinMaxScaler()
scaler.fit(data)    

print(scaler.transform([[2, 2]]))
Out>>> [[ 1.5  0. ]]

// This is what you need
print(scaler.inverse_transform([[ 1.5  0. ]]))
Out>>> [[ 2.0  2.0]]
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