Transcription of An Introduction to the WEKA Data Mining System
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An Introduction to the WEKA Data Mining System
An Introduction to the WEKA Data Mining SystemZdravko Markov Central Connecticut State Russell University of Mining "Drowning in Data yet Starving for Knowledge" ??? "Computers have promised us a fountain of wisdom but delivered a flood of data"William J. Frawley, Gregory Piatetsky-Shapiro, and Christopher J. Matheus Data Mining : "The non trivial extraction of implicit, previously unknown, and potentiallyuseful information from data"William J Frawley, Gregory Piatetsky-Shapiro and Christopher J Matheus Data Mining finds valuable information hidden in large volumes of data.
Distance(test,X) 1 2 2 2 2 … 4 X 2 8 9 11 12 … 10 • K-nearest neighbor (KNN, IBk) Take the class of the nearest neighbor or the majority class among K neighbors K=1 -> no K=3 -> no K=5 -> yes K=14 -> yes (Majority predictor, ZeroR) • Distance is calculated as the number of different attribute values • Euclidean distance for numeric ...
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