Identifying influential features with factor prioritization

The Morris Method is one of several global sensitivity analysis methods that range from simpler Fractional Factorial to complicated Monte Carlo Filtering. Morris is somewhere in-between this spectrum, falling into two categories. It uses one-at-a-time sampling, which means that only one value changes between consecutive simulations. It's also elementary effects (EE), which means that it doesn't quantify the exact effect of a factor in a model but rather gauges its importance and relationship with other factors. By the way, factor is just another word for a feature or variable that's commonly used in applied statistics. To be consistent with the related theory, we will use this word in this and the next section.

Another property of Morris is that it's less computationally expensive than the variance-based methods we will study next. It can provide more insights than simpler and less costly methods such as regression...