Using Multi Layered Perceptron (MLP) neural network for “Iris” and “Glass” datasets to study the effect of number of neurons in the hidden layer, number of hidden layers, on classification performance.
Analysing the effect of number of neurons in hidden layers for Iris dataset
Analysing the effect of number of neurons in hidden layers for Glass identification dataset
Analysing the effect of number of neurons in hidden layers on train and test sets for Iris dataset
the star signs corresponds to test-set and the plus signs corresponds to the training-set
Analysing the effect of number of neurons in hidden layers on train and test sets for Glass identification dataset
the star signs corresponds to test-set and the plus signs corresponds to the training-set
