1. kNN- select variables based on pca results- normalize (max-min / z norm) each variable- scatter datapoints into space- datapoints -> label O, label X group split- apply kNN alg -> classify label X group, using k nearest datapoints(label O group) * k is odd number! -> to escape the situation where k nearest datapoints show 50:50 proportion of two classes* supervised learning: must use labeled ..