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

Eds Iantovics, D Rˇadoiu, M Mˇaru¸steri, Mˇaru¸ Mˇaru¸steri, M Dehmer, Maria Muntean, Ioan Ilean˘, Corina Rotar, Mircea Rˆıs¸teiu, Rˆıs Rˆıs¸teiu
2010 Special Issue on Complexity in Sciences and Artificial Intelligence   unpublished
This paper presents three data mining techniques applied on a SCADA system data repository: Na¨ıveNa¨ıve Bayes, k-Nearest Neighbor and Decision Trees. A conclusion that k-Nearest Neighbor is a suitable method to classify the large amount of data considered is made finally according to the mining result and its reasonable explanation. The experiments are built on the training data set and evaluated using the new test set with machine learning tool WEKA.
fatcat:mcdyly53bzdjzcggtqekl2nbhq