machine learning - Confusion between Binary_crossentropy and Categorical_crossentropy -


i doing binary class classification using deep neural network. whenever using binary_crossentropy model not giving accuracy (it closer random prediction). if use categorical crossentropy making size of output layer 2, getting accuracy in 1 epoch close 0.90. can please explain happening here?

i have problem while trying use binary_crossentropy softmax activation in output layer. far know, softmax give probability of each class, if output layer has 2 nodes, p(x1), p(x2) , x1 + x2 = x. therefore, if have 1 output node, equals 1.0 (100%), that's why have close random prediction (honestly, close category distribution in evaluation set).

try changing activation method sigmoid or relu.


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