k-NN is a classification algorithm that uses (k) for the number of neighbours to determine what class an item will belong to. To determine the neighbours to be used the algorithm uses a distance / similarity score function, in this example (Euclidian Distance).
PCI takes it a little further to help with accuracy in some scenarios. This includes the usage of a weighted average of the neighbours, as well as then using either simulated annealing or genetic algorithms to determine the best weights, building on Optimization techniques - Simulated Annealing & Genetic Algorithms
Read full article from Zen in the art of IT: Creating a price model using k-Nearest Neighbours + Genetic Algorithm
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