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model accuracy #13

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xuzhang5788 opened this issue Apr 30, 2018 · 0 comments

xuzhang5788 commented Apr 30, 2018

in your train_*.py, at the end, your code is like this:
yPreds = model.predict(testX)
yPred = np.argmax(yPreds, axis=1)
yTrue = testY

accuracy = metrics.accuracy_score(yTrue, yPred) * 100
error = 100 - accuracy
print("Accuracy : ", accuracy)
print("Error : ", error)

I don't understand why you used np.argmax(Preds, axis=1). I think you should use
yPreds[yPreds >= 0.5] = 1
yPreds[yPreds < 0.5] = 0
yPred = yPreds
When you used model.predict, which weights did you use? the last one or the best one?

Many thanks

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