Hi all,
I ran a simple decision tree on a credit dataset (with fake data), basically for predicting the outcome of a credi evaluation process, with the class variable beiong valued Bad/Good.
The model scores reasonably well.
I tried to did the same and train a neural network MLP Percepton on the same data set, and what I've got is a 100% error rate on the confusion matrix.
I included the workflow I've build , can someone have a quick look at it and tell me where is the error ? Thanks a lot in advance!!
PS: I'm a newbie with NN....
Giovanni