I'm trying to separate classes in 3D space, the data are as in the sketch below:
There are 3 classes: 0,1,2; and with the look into the sketch, it seems that I need 3 planes to separate the classes, thus how many hidden layers should be in the DNN? Any roughly how many neurons in each layer?
Some say the number of hidden layers is roughly the number of separation times, so I put 3 hidden layers and it worked! But any reasons behind that simple measure?