When Skewness Becomes a Compass for Hidden Data Clusters
Finding Order in the Unlabeled Chaos In the vast ocean of data, one of the most fundamental tasks is to separate the signal from the noise—to distinguish between groups or clusters hidden within the data. Traditionally, this requires knowing which data points belong to which group, a luxury often unavailable in real-world scenarios. But what…