NaN loss when training regression network

Question

I have a data matrix in \"one-hot encoding\" (all ones and zeros) with 260,000 rows and 35 columns. I am using Keras to train a simple neural network to predict a continuou

Answer 1

Was getting NaN for my classification network. Answering here as it might help someone.

Had made a blunder -

Number of classes in training labels was 5. i.e. from 0 to 4.

In the last dense layer of classification had 4 nodes which means 4 classes which is the issue.

Chaging the number of nodes in the last layer of network to 5 solved the issue for me.