Parameter search
import numpy as np
from sklearn.grid_search import RandomizedSearchCV
params = {
'randomizedpca__n_components': [5, 10, 20],
'svc__C': np.logspace(-3, 3, 7),
'svc__gamma': np.logspace(-6, 0, 7),
}
search = RandomizedSearchCV(pipeline, params,
n_iter=30, cv=5)
search.fit(X_train, y_train)
# search.best_params_, search.grid_scores_