I've been getting more interesting progress in my machine learning this Post Circuit Breaker (hence PCB) season. For rookies who are delving into darker recesses of machine learning, a low hanging fruit to improve your AI programming skills is K-nearest neighbour algorithm (KNN). So this article is a discussion on my attempts to use the K-nearest neighbour algorithm during the Post circuit breaker era. (Hence KNN PCB !) One question I always had for myself is how do we categorise blue-chips into clusters of stocks so that we can think about them in an easier manner. Intuitively, I tell my students that you can get a firmer grasp of the STI if you think about Banks, REITs, Developers and Jardine counters. But the weakness of this approach is that the four categories I mentioned only cover only 16 stocks, what about the remaining 14? KNN is a method to train a...