Python smile_dataset_clear示例

示例#1

文件： classification.py 项目： zackcd/CSCI567---Machine-Learning

def run_multiclass():
    from data_loader import smile_dataset_clear, \
                            smile_dataset_blur, \
                            data_loader_mnist
    import time
    datasets = [(smile_dataset_clear(), 'Clear smile data', 3),
                (smile_dataset_blur(), 'Blur smile data', 3),
                (data_loader_mnist(), 'MNIST', 10)]

    for data, name, num_classes in datasets:
        print('%s: %d class classification' % (name, num_classes))
        X_train, X_test, y_train, y_test = data
        for gd_type in ["sgd", "gd"]:
            s = time.time()
            w, b = sol.multiclass_train(X_train,
                                        y_train,
                                        C=num_classes,
                                        gd_type=gd_type)
            print(gd_type + ' training time: %0.6f seconds' %
                  (time.time() - s))
            train_preds = sol.multiclass_predict(X_train, w=w, b=b)
            preds = sol.multiclass_predict(X_test, w=w, b=b)
            print('train acc: %f, test acc: %f' % (accuracy_score(
                y_train, train_preds), accuracy_score(y_test, preds)))
        print()

示例#2

文件： test.py 项目： ashutoshkmr21/CSCI567

from data_loader import smile_dataset_clear, \
                            smile_dataset_blur, \
                            data_loader_mnist
import time
datasets = [(smile_dataset_clear(), 'Clear smile data', 3),
            (smile_dataset_blur(), 'Blur smile data', 3),
            (data_loader_mnist(), 'MNIST', 10)]

for data, name, num_classes in datasets:
    print('%s: %d class classification' % (name, num_classes))
    X_train, X_test, y_train, y_test = data