effect of increasing C in svm code example

Example: best value of c in linear svm

np.random.seed(222)
# train dataset
X, y = make_classification(
    n_samples=10000, 
    n_features=10,
    n_informative=10,
    n_redundant=0,
    weights=[0.3,0.7],
    class_sep=0.7,
    flip_y=0.35) # the default value for flip_y is 0.01, or 1%
X_train, _ , y_train, _ = train_test_split(X, y, test_size=0.25)

np.random.seed(222)
# test dataset
X, y = make_classification(
    n_samples=10000, 
    n_features=10,
    n_informative=10,
    n_redundant=0,
    weights=[0.3,0.7],
    class_sep=0.7,
    flip_y=0.0)
_, X_test , _ , y_test = train_test_split(X, y, test_size=0.25)