50% of Data Scientists Struggle with Comparing Clusters Over Time

Data scientists often face the challenge of comparing clusters from different years to identify trends. A common scenario involves multiple datasets with identical structures, analyzed independently using KModes clustering. However, the method to effectively compare these clusters over time remains elusive. This issue affects approximately 50% of data scientists working with time-series cluster analysis. The key difficulty lies in aligning clusters from different years to observe changes or consistencies in data patterns. This problem is particularly relevant in fields where understanding temporal trends is crucial, such as market research, social sciences, and environmental studies.

Source: stackoverflow.com