MinMaxScaler#
- class chemotools.scale.MinMaxScaler(use_min: bool = True)[ソース]
ベースクラス:
TransformerMixin,OneToOneFeatureMixin,BaseEstimatorA transformer that scales the input data by subtracting the minimum and dividing by the difference between the maximum and the minimum. When the use_min parameter is False, the data is scaled by the maximum.
- パラメータ:
use_min (bool, default=True) -- The normalization to use. If True, the data is subtracted by the minimum and scaled by the maximum. If False, the data is scaled by the maximum.
- 変数:
n_features_in (int) -- The number of features in the input data.
サンプル
>>> from chemotools.datasets import load_fermentation_train >>> from chemotools.scale import MinMaxScaler >>> # Load sample data >>> X, _ = load_fermentation_train() >>> # Initialize MinMaxScaler >>> scaler = MinMaxScaler() MinMaxScaler() >>> # Fit and transform the data >>> X_scaled = scaler.fit_transform(X)
- fit(X: ndarray, y=None) MinMaxScaler[ソース]
Fit the transformer to the input data.
- パラメータ:
X (np.ndarray of shape (n_samples, n_features)) -- The input data to fit the transformer to.
y (None) -- Ignored to align with API.
- 戻り値:
self -- The fitted transformer.
- 戻り値の型:
MinMaxScaler
- transform(X: ndarray, y=None) ndarray[ソース]
Transform the input data by scaling it.
- パラメータ:
X (np.ndarray of shape (n_samples, n_features)) -- The input data to transform.
y (None) -- Ignored to align with API.
- 戻り値:
X_transformed -- The transformed data.
- 戻り値の型:
np.ndarray of shape (n_samples, n_features)