Interpreting fraction of zero weights in TensorFlow

I am using the TensorFlow to do a simple linear classification using logistic regression. The graph included from the TensorBoard displays what they call the fraction of zero weights. How do I interpret this in terms of model evaluation? I am assuming this is good since I got the good results in terms of loss, precision, recall, etc but not sure.

Thank you.

• Set your smoothing to zero. The fraction is 0 at step 100, which appears to be the first real time it is sampled – kbrose Sep 26 '19 at 23:47

If you are performing linear (logistic) regression your weights are simply your $$\beta_i$$. If none of them are $$0$$ that simply means all features are 'important' to some degree.