I having a data set that contains the distance and channel gain of the users.
I wnat to group the users into clusters such that the throughput needs to get maximized.
Therefore i need to feed distance and channel gain of the users as input to the input layer neural network,where the grouping needs to performed in the hidden layers and throughput maximization needs to be done in the output layer.
I have seen some sample matlab code which has the input and output in the training section and the model is trained using the data.
then in the testing stage,the model is tested to obtain the correct output.
But in my case the output is the throughput wich needs to be maximized by adjusting the weights in the hidden layers.
could anyone please help me on this.Or is there any other way the throughput can be maximized. .