Knowledge Discovery in a Scada System Database
نویسندگان
چکیده
This paper presents three data mining techniques applied on a SCADA system data repository: Näıve 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.
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