18872
6691
sklearn.preprocessing.data.MinMaxScaler
sklearn.MinMaxScaler
sklearn.preprocessing.data.MinMaxScaler
7
openml==0.12.2,sklearn==0.18.1
Transforms features by scaling each feature to a given range.
This estimator scales and translates each feature individually such
that it is in the given range on the training set, i.e. between
zero and one.
The transformation is given by::
X_std = (X - X.min(axis=0)) / (X.max(axis=0) - X.min(axis=0))
X_scaled = X_std * (max - min) + min
where min, max = feature_range.
This transformation is often used as an alternative to zero mean,
unit variance scaling.
2021-08-13T19:19:24
English
sklearn==0.18.1
numpy>=1.6.1
scipy>=0.9
copy
boolean
true
Set to False to perform inplace row normalization and avoid a
copy (if the input is already a numpy array).
feature_range
tuple
[0, 1]
Desired range of transformed data
openml-python
python
scikit-learn
sklearn
sklearn_0.18.1