Machine Learning, Data Science, Python, Support Vector Machine, Artificial Intelligence.
axis='columns') y = df.target x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2) model = SVC(C =2, gamma=10) model.fit(x_train, y_train) model.score(x_test, y_test) .93 is great, but we can use sklearn’s grid search class to calculate even better values for gamma & C. import