Just a thought: I don't see the implementation of the algorithm here, but if you're using the values of individual cards scaled to 1, then you are saying that v

Just a thought: I don't see the implementation of the algorithm here, but if you're using the values of individual cards scaled to 1, then you are saying that v(A) - v(K) = v(8) - v(7) which seems absurd Instantiating the features correctly is crucial to getting good neural network accuracy. It might be the case that a thermometer representation for the card value is more appropriate. The thermometer representation is that there are thirteen bit-values, and the first n values are on for the value n. Using this sort of input representation, the network can model the non-linear relationship between different card values, instead of assuming a strictly linear correlation.