I examined the data to determine the pattern of police shootings in various states across the United States. In addition, I am looking for a data processing method that will assist me in identifying missing values or outliers by imputing them with cluster-specific statistics. I primarily uncover underlying structures in data using the clustering technique, which aids in data reduction, supports segmentation, classification, and anomaly detection, and discovers applications in a wide range of domains.

I have came across two other clustering methods:

The mode-seeking algorithm is Mean Shift Clustering. Mean Shift finds cluster centres by shifting each data point in the direction of the density function mode repeatedly. It is useful for identifying patterns in data distribution.

Spectral clustering involves projecting data points into a lower-dimensional space and clustering them using the eigenvalues of a similarity matrix. It is useful for non-convex clusters.