Should I use highly skewed features in my model?

Many of my features are highly skewed as you can see below in the figure. Should I be using such skewed data for modeling purposes? If I cannot, then is there any way to integrate such features in my model? Since most of my features have a distribution plot like this, can I make a good machine learning model from such data?

• How many distinct values? Exact zeros? Can you show a plot of its log (or maybe of $\log(x+1)$? – kjetil b halvorsen Jul 24 at 17:30

Classifiers like (deep) neural networks, discriminant analysis, support vector machines, logistic regression - they all use some sort of (local) distance measure. For such models a log-transformation or a power transformation (e.g. $$\sqrt{x}$$) are highly recommended for your use case.