Hi Madhurima, The confusion matrix you get in the end is a "bad" result. You should have the values on the main diagonal higher than those on the off diagonal. Looking at the iteration results you may see that the nnet did not learn too much from your data. There are lots of possible problems: A) there is no relation between the class variable and the predictor you use B) the model is not well designed (too few or too many hidden nodes for eg.) Send the data you want more detail. Laurentiu >>Hello Everybody, >>I would like to know how to interpret the result of nnet function of R. >>My result looks like this: # weights: 24 initial value 6.533893 iter 10 value 4.616299 iter 20 value 4.616120 iter 30 value 4.616109 iter 30 value 4.616109 final value 4.616109 converged cres true 1 1 10 2 3 Can anyone please help me asap?