I have a model I've trained on ~3400 features with ~500 samples (40:20:20 train:test:val) that I've calculated MDA on using the eli5 package. However, all the features are zero when I calculate this with the train or test dataset.
My dataset is a fairly sparse dataset with mostly zeros and I'm trying to classify disease. Here is a sample:
The model is a random forest that is predicting disease class (0 or 1). the dataset is imbalanced with appx (90% 0 and 10% 1)
My model accuracies are as follows:
confusion matrix for test [[76 0] [ 0 8]]
these are my gini importances:
MDAs are all zero for testing and training. Why is that and what does it mean for the generalizability of the model?