KMNIST kNN

[dzisandy]

Adding PCA dimension reduction produces better Test Accuracy
x_train = x_train.reshape(-1, 784)
x_test = x_test.reshape(-1, 784)
After this code rows:
pca = PCA(n_components= 60, random_state= 0 )
x_train = pca.fit_transform(x_train)
x_test = pca.transform(x_test)
The resulting is Test accuracy: 0.9398

[hardmaru]

Thanks, that’s a good datapoint to know!

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On Tue, Mar 26, 2019 at 8:25 AM Andrei Dzis ***@***.***> wrote: Closed #10 <#10>. — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#10 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AGBoHlSaYoK1E5J_aVbVI3pW5nCGBo2vks5vaVr2gaJpZM4cJ4xh> .

[mxbi]

Added, it would be good to also have data points for MNIST and K-49

[dzisandy]

@mxbi Thanks for credit!

[mxbi]

See also #13 for K-49 and MNIST code/details