Final submission of my haiti displaced individual classification project for DS6030 in UVA's MS Data Science program.

My goal in this analysis was to determine the optimal model for locating displaced people. To determine those models, I focused on two statistics; accuracy, and false negative rate (FNR). Given the context of the situation, I believed the FNR to be a very important metric, much more than the false positive rate (FPR), because I wanted to make sure no displaced individual was being overlooked. I would much rather have over-classified and found no one at a certain location than under-classify and not provide aid to someone in need. But, it is important to note that these efforts still needed to be made in a timely manner, so grossly over-classifying to get the smallest FNR was not the optimal solution. So, a combination of accuracy, FNR, and FPR was used to determine these models.