pipelines_001.py

from sklearn.model_selection import train_test_split
from sklearn.datasets import load_breast_cancer

cancer = load_breast_cancer()
X_train, X_test, y_train, y_test = train_test_split(
    cancer.data, cancer.target, random_state=0)

from sklearn.pipeline import Pipeline
pipe = Pipeline([('scaler', MinMaxScaler()), ('svm', SVC())])
pipe.fit(X_train, y_train)

from sklearn.model_selection import GridSearchCV

param_grid = {'C':[0.001, 0.01, 0.1, 1, 10, 100],
              'gamma': [0.001, 0.01, 0.1, 1, 10, 100]}
grid = GridSearchCV(SVC(), param_grid=param_grid, cv=5)
grid.fit(X_train, y_train)

print("Best cross-validation accuracy: {:.2f}".format(grid.best_score_))
print("Test set score: {:.2f}".format(grid.score(X_test, y_test)))
print("Best parameters: ", grid.best_params_)