A cost function comprising separability and predictability indexes is then calculated, which balances between the enhancement of separability among different partitions and the improvement of predictability within each partition. PARC terminates when either the difference in the value of the cost function between two consecutive evaluations falls below a predefined tolerance, or the number of iterations surpasses a predetermined maximum limit. Otherwise, PARC reassigns samples to K updated clusters based on the newly fitted PWA separation functions and then iterates the procedure until termination criteria are met.