Quantifying uncertainty and cost sensitivity with factor fixing
With the Morris indices, it became evident that all the factors are non-linear or non-monotonic. There's a high degree of interactivity between them – as expected! It should be no surprise that climate factors (temp, rain_1h, snow_1h, and cloud_coverage) are likely multicollinear with hr. There are also patterns to be found between hr, is_holiday, and dow and the target. Many of these factors most definitely don't have a monotonic relationship with the target. We know this already. For instance, traffic doesn't consistently increase as hours increase throughout the day. That's not the case between days of the week either!
However, we didn't know to what degree is_holiday and temp impacted the model, particularly during the crew's working hours, which was an important insight. That being said, factor prioritization with Morris indices is usually to be taken as a starting point or "...
