What loss function in keras should I chose for binary_crossentropy or categorical_crossentropy?
I have data like : $w1,w2,w3,w2,w2,w1,w3,w5,w9,w5,w4...$
I want to predict sequence:
input: $w1,w2,w3$ -> $LSTM$ -> get output: $w2,w2,w1$
I encoded the symbols $w1,w2...$ by obe-hot-encoding
So the input of the model is : $[[1,0,0],[0,1,0],[0,0,1]]$
The output of the model is : $[[0,1,0],[0,1,0],[1,0,0]]$
categorical_crossentropy
. Also, elaborate your question with some information in order to receive proper guidance. $\endgroup$