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1) Our aim is to distinguish whether the engineering faculty student is from CE department or from IE department according to their maturity, social activity

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1) Our aim is to distinguish whether the engineering faculty student is from CE 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 student dept. maturity social activity rel. with performance friends rel. with teachers Mustafa Ahmet Aycl Recai Bahadr Mehmet Dilek Hasan CE CE CE CE IE EE EE EE 3 3 4 5 3 3 2 3 4 4 4 5 2 3 3 2 5 4 4 3 4 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 4 3 4)',(4 4 3 3)' and (3 3 5 3)' and also by selecting the functions as G(x,x)=etx-x)"[48-4) where x;'s are the centers for the RBF network and is the diagonal covariance matrix obtained using all the training data. Use one output node for the output layer and assume the desired value for CE department is 1 and the desired value for IE department is -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 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 student dept. maturity social activity rel. with performance friends rel. with teachers Mustafa Ahmet Aycl Recai Bahadr Mehmet Dilek Hasan CE CE CE CE IE EE EE EE 3 3 4 5 3 3 2 3 4 4 4 5 2 3 3 2 5 4 4 3 4 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 4 3 4)',(4 4 3 3)' and (3 3 5 3)' and also by selecting the functions as G(x,x)=etx-x)"[48-4) where x;'s are the centers for the RBF network and is the diagonal covariance matrix obtained using all the training data. Use one output node for the output layer and assume the desired value for CE department is 1 and the desired value for IE department is -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

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