DATA MINING LEARNING MODELS AND ALGORITHMS ON A SCADA SYSTEM DATA REPOSITORY

This paper presents three data mining techniques appliedon a SCADA system data repository: Naijve Bayes, k-Nearest Neighbor andDecision Trees. A conclusion that k-Nearest Neighbor is a suitable method to classify thelarge amount of data considered is made ¯nally according to the mining resultand its reasonable explanation. The experiments are built on the training data set and evaluated using thenew test set with machine learning tool WEKA