k nearest Neighbors classifies or predicts quantitative value for new samples using voting/average values of the nearest neighbors of the analyzed sample. Prior to model training all descriptors are normalized to standard deviation of 1 and mean value of 0.

Algorithm parameters include

• Distance (Euclidian distance, Pearson correlation)

• KNN neighbors
  The specified number of nearest neighbors will be used, unless this value is 0. In the later case this number will be optimized in range from 1 to Max KNN neighbors.

• Max KNN neighbors.
  Specifies maximum number of nearest neighbors for automatic determination of the KNN neighbors number.