So I have a dataset that I've been performing machine learning algorithms on. I've performed MLR, stepwise regression, SVM and Random Forest on a dataset that is 180 x 160. I'm modelling one variable against 159 other variables, with 179 cases. It's all regression modelling. I've been using the caret package in which I use the train function to do 10 fold cross validation 10 times with the different machine learning algorithms. I was told to read up a paper that had used neural network models instead and got better results, so I've been trying to find a way of doing the same thing but with a neural network model instead. So I have a dataset that I've been performing m