Week 6 Review: 7/9 - 7/13
The PCA method from week 5 was modified and implemented to select features to be used for the remainder of the project. Five prominent features are now attributed to each subset. After selecting the features, the data was normalized using MinMaxScaler. Each subset was grouped into 30-minute windows for clustering. I used k-means on each window separately and created lists of centroid locations and group labels. With the help of Alina, I was able to find and list the degree changes of centroids between windows. Alex Sim, a mentor of mine in the SDM group, published several papers using this idea of degree change. The degree change is defined as the sum of the distances each centroid moves from one window to another. The following visual help demonstrate the proposed formula. The previous window is on the left and the current window is on the right. The diagonal black line segments show the distance each centroid has moved from the previous window to the current window. Consid...