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
I had similar issue with my logloss, MAE and others being all NA's. I looked into the data and found, I had few features with NA's in them. I imputed NA's with approximate values and was able to solve the issue.