1) Our aim is to distinguish whether the engineering faculty student is from CE department, from EE department or from IE department according to their maturity, social activity performance, relation with their friends, and relation with their teachers. To achieve this goal, we used the set of data as given below for training name of a dept. maturity social activity rel. with performance friends rel. with teachers student Mustafa Ahmet Aycl Recai Bahadr Mehmet Dilek Hasan CE CE CE IE IE EE EE EE 3 3 4 5 4 3 2 3 4 4 4 5 5 3 3 2 5 4 4 3 3 4 5 5 5 4 5 4 3 3 4 3 Use Radial Basis Function (RBF) network to model the problem given above by taking the 3 centers as (3 3 3 4)',(4 4 3 3) and (3 4 5 3) and also by selecting the functions as G(x,x)=e (x-1){ '(1-21) where xi's are the centers for the RBF network and is the diagonal covariance matrix obtained using all the training data. For the RBF network that you are going to use , use 3 different outputs in such a way that each output will represent one class (department) as shown below desired outputs output(node) CE IE EE 1 1 -1 - 1 2 - 1 1 -1 3 -1 - 1 1 Obtain the matrix form of the solution for the weights that is given as Gw-d Hint: : Use all data as a training data. 1) Our aim is to distinguish whether the engineering faculty student is from CE department, from EE department or from IE department according to their maturity, social activity performance, relation with their friends, and relation with their teachers. To achieve this goal, we used the set of data as given below for training name of a dept. maturity social activity rel. with performance friends rel. with teachers student Mustafa Ahmet Aycl Recai Bahadr Mehmet Dilek Hasan CE CE CE IE IE EE EE EE 3 3 4 5 4 3 2 3 4 4 4 5 5 3 3 2 5 4 4 3 3 4 5 5 5 4 5 4 3 3 4 3 Use Radial Basis Function (RBF) network to model the problem given above by taking the 3 centers as (3 3 3 4)',(4 4 3 3) and (3 4 5 3) and also by selecting the functions as G(x,x)=e (x-1){ '(1-21) where xi's are the centers for the RBF network and is the diagonal covariance matrix obtained using all the training data. For the RBF network that you are going to use , use 3 different outputs in such a way that each output will represent one class (department) as shown below desired outputs output(node) CE IE EE 1 1 -1 - 1 2 - 1 1 -1 3 -1 - 1 1 Obtain the matrix form of the solution for the weights that is given as Gw-d Hint: : Use all data as a training data