Comparison of classification performance of kNN and WKNN algorithms

Özet

In this study, K nearest neighbor (kNN) algorithm which is the most popular and widely used among the machine learning classification algorithms and the weighted kNN (WKNN) algorithm which takes the weight of the feature index into consideration, are used. As the weighting method, a weighting is made by taking the inverse of the distance squared (w = 1 / d2).  The confusion matrix of the data sets was created by applying the algorithms to five data sets via MATLAB program and the classification success was compared by conducting performance measurements of algorithms. It was observed that in two of the five data sets used in the study kNN algorithm turned out to make a more successful classification than WKNN while in three data sets the WKNN algorithm performed a more successful classification than the kNN.