svm_oop.py 文件源码

def get_data(iris):
# Only petal length and petal width considered
    X = iris.data[:, [2, 3]]
    y = iris.target

# Place the iris data into a pandas dataframe
    iris_df = pd.DataFrame(iris.data[:, [2, 3]], columns=iris.feature_names[2:])

# View the data
    print(iris_df.head())

# Print the classes of the dataset
    print('\n' + 'The classes in this data are ' + str(np.unique(y)))
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=.3, random_state=0)

    print('Training set are {} samples  and Test set are {} samples'.format(
    X_train.shape[0], X_test.shape[0]))
    print()
    return(X_train, X_test, y_train, y_test,iris_df, X,y)
##scale data before training it