Nearest Centroid Classifier with Outlier Removal for Classification

Abstract

Classification method is misled by outlier. However, there are few research of classification with outlier removal, especially for Nearest Centroid Classifier Method. The proposed methodology consists of two stages. First, preprocess the data with outlier removal, removes points which are far from the corresponding centroid. Second, classify the outlier removed data. The experiment covers six data sets which have different characteristic. The results indicate that outlier removal as preprocessing method provide better result for improving Nearest Centroid Classifier performance on most data set.