scikit grid search

scikit_grid_search.py

from sklearn.pipeline import Pipeline
from sklearn.linear_model import ElasticNet
from sklearn.compose import ColumnTransformer
from sklearn.preprocessing import StandardScaler, OneHotEncoder
from sklearn.model_selection import GridSearchCV

pipeline = Pipeline(steps=[
    ('preprocess', ColumnTransformer(transformers=[
        ('num', StandardScaler(), numeric_feat),
        ('cat', OneHotEncoder(handle_unknown='ignore', sparse=False), categorical_feat),
    ])),
    ('clf', ElasticNet(normalize=False, max_iter=100)),
])

# this is our grid
params = {
    'clf__l1_ratio': np.arange(0, 1.01, 0.01),
    'clf__alpha': [0, 0.5, 1, 2],
}

grid_search = GridSearchCV(pipeline, params, cv=3, n_jobs=-1, scoring='neg_mean_squared_error')