Ordinal – Variables with an ordered series, such as blood group, performance etc. Numeric attribute Nominal attribute Nominal – variables with no inherent order or ranking sequence such as Gender, Race etc. Preprocess data Classification Attribute Selection KnowledgeFlowĭata can be imported from a file in various formats: ARFF, CSV, C4.5, binary Data can also be read from a URL or from an SQL database (using JDBC) Pre-processing tools in WEKA are called “filters” WEKA contains filters for: Discretization, normalization, resampling, attribute selection, transforming and combining attributes, …Ĩ WEKA “arff” format age numeric sex 63,male,typ_angina,233,no,not_present 67,male,asympt,286,yes,present 67,male,asympt,229,yes,present 38,female,non_anginal,?,no,not_present. “The Experimenter” (experimental environment) “The KnowledgeFlow” (process model inspired interface) “Simple CLI” (Command Line interface)Ħ Todays Workshop! What is WEKA? The Explorer: KnowledgeFlow Website: Support multiple platforms (written in java): Windows, Mac OS X and LinuxĤ Main Features 49 data preprocessing toolsħ6 classification/regression algorithms 8 clustering algorithms 3 algorithms for finding association rules 15 attribute/subset evaluators + 10 search algorithms for feature selectionĥ WEKA GUI Main components “The Explorer” (exploratory data analysis) Weka is also a bird found only on the islands of New Zealand. It’s a data mining/machine learning tool developed by Department of Computer Science, University of Waikato, New Zealand. Preprocess data Classification Clustering Attribute Selection Data Visualization KnowledgeFlow Visual Modelerģ What is WEKA? Waikato Environment for Knowledge Analysis Sampath Jayarathna Cal Poly PomonaĢ Todays Workshop! What is WEKA? The Explorer: KnowledgeFlow CS 795/895 Introduction to Data Science Lecture 10 – Introduction to Weka Dr.

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