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| data = np.load('files/mnist_data.npy').astype(float) | |
| train_y = data[0:5000, 0] | |
| train_x = data[0:5000, 1:] | |
| test_y = data[0:1000, 0] | |
| test_x = data[0:1000, 1:] | |
| RBF_CLASSIFIER = RBF(train_x, train_y, test_x, test_y, num_of_classes=10, | |
| k=500, std_from_clusters=False) | |
| RBF_CLASSIFIER.fit() |
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