GridSearchCV(cv=TimeSeriesSplit(gap=0, max_train_size=None, n_splits=5, test_size=14),
estimator=Pipeline(steps=[('linear_feature_engineering',
Pipeline(steps=[('linear_preprocessor',
ColumnTransformer(remainder='passthrough',
transformers=[('cat',
Pipeline(steps=[('one_hot',
OneHotEncoder())]),
['season',
'mnth',
'holiday',
'weekday',
'workingday',
'weathersit']...
param_grid={'linear_regressor__alpha': array([1.00000000e-03, 2.06913808e-03, 4.28133240e-03, 8.85866790e-03,
1.83298071e-02, 3.79269019e-02, 7.84759970e-02, 1.62377674e-01,
3.35981829e-01, 6.95192796e-01, 1.43844989e+00, 2.97635144e+00,
6.15848211e+00, 1.27427499e+01, 2.63665090e+01, 5.45559478e+01,
1.12883789e+02, 2.33572147e+02, 4.83293024e+02, 1.00000000e+03])},
scoring='neg_root_mean_squared_error')Pipeline(steps=[('linear_preprocessor',
ColumnTransformer(remainder='passthrough',
transformers=[('cat',
Pipeline(steps=[('one_hot',
OneHotEncoder())]),
['season', 'mnth', 'holiday',
'weekday', 'workingday',
'weathersit']),
('num',
Pipeline(steps=[('scaler',
StandardScaler())]),
['temp', 'hum', 'windspeed',
'days_since_2011',
'yr'])])),
('polynomial',
PolynomialFeatures(include_bias=False, interaction_only=True)),
('variance_threshold', VarianceThreshold())])ColumnTransformer(remainder='passthrough',
transformers=[('cat',
Pipeline(steps=[('one_hot', OneHotEncoder())]),
['season', 'mnth', 'holiday', 'weekday',
'workingday', 'weathersit']),
('num',
Pipeline(steps=[('scaler', StandardScaler())]),
['temp', 'hum', 'windspeed', 'days_since_2011',
'yr'])])['season', 'mnth', 'holiday', 'weekday', 'workingday', 'weathersit']
OneHotEncoder()
['temp', 'hum', 'windspeed', 'days_since_2011', 'yr']
StandardScaler()
passthrough
PolynomialFeatures(include_bias=False, interaction_only=True)
VarianceThreshold()
Lasso()