Data Mining - Neural Network - Data Mining Assignment Help

Internal Code : I_AH_CFFA_AAF

Data Mining Assignment Help

TASK Describe the data encoding that is required for this task. How many outputs and how many inputs will there be? What scaling or normalization is required? Modify your script from part 1 to generate the necessary training, validation and test files. You can use Weka to normalize all of the numeric attributes except for the class, ie weight attribute. You will need to write a suitable program to scale the weight to the range [0,1] and another one to reverse scale the neural net outputs to get the mean absolute error. Using Javanns carry out 5 train and test runs for a network with 5 hidden nodes. Comment on the variation in the training runs and the degree of overfitting. Experiment with different numbers of hidden nodes. What seems to be the right number of hidden nodes for this problem? For 5 hidden nodes, explore different values of the learning rate. What do you conclude? Change the learning function to backprop-momentum. Explore different combinations of learning rate and momentum. What do you conclude? Perform a run with 5 hidden nodes and no validation data. Stop training when the MSE is no longer changing. Get the error on the training and test data. Com-ment on the degree of overfitting. Compare the mean absolute error of the neural classifiers with the mean absolute error of Weka M5P and MultiLayerPerceptron.