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Florida International University COP 4770 Introduction of Weka.

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Presentation on theme: "Florida International University COP 4770 Introduction of Weka."— Presentation transcript:

1 Florida International University COP 4770 Introduction of Weka

2 Outline Introduction Take a tour Input & output format Introduction of Weka

3 Whats Weka Waikato Environment for Knowledge Analysis (WEKA) Developed by the Department of Computer Science, University of Waikato, New Zealand Machine learning/data mining software written in Java (distributed under the GNU Public License) Used for research, education, and applications Introduction of Weka

4 Weka Homepage To download WEKA 3.6.3: windows/3.6.3/weka exe/download windows/3.6.3/weka exe/download Introduction of Weka

5 Installation Weka To run: weka exe Introduction of Weka

6 Main Features Schemes for classification include: decision trees, rule learners, naive Bayes, decision tables, locally weighted regression, SVMs, instance-based learners, logistic regression, voted perceptrons, multi-layer perceptron Schemes for numeric prediction include: linear regression, model tree generators, locally weighted regression, instance-based learners, decision tables, multi-layer perceptron Meta-schemes include: Bagging, boosting, stacking, regression via classification, classification via regression, cost sensitive classification Schemes for clustering: EM and Cobweb Schemes for feature selection: Ranker…. Introduction of Weka

7 Take a tour Getting start Start All Programs Weka Weka 3.6 Click to Start a Tour! Introduction of Weka

8 Take a tour Weka Explorer Screenshot Filter Load Feature Info Label Info Introduction of Weka

9 Take a tour Click Open file ; Choose Weka-3.6/data/*.arff; Click Open. Introduction of Weka

10 Take a tour Filter Filters can be used to change data files; AttributeSelection lets you select a set of attributes; Other filters Discretize: Discretizes a range of numeric attributes in the dataset into nominal attributes; NominalToBinary: Converts nominal attributes into binary ones, replacing each attribute with k values with k-1 new binary attributes; … Introduction of Weka

11 Take a tour 2D Visualization Visualize Attributes Introduction of Weka

12 Take a tour Classifier - 1 Introduction of Weka

13 Take a tour Classifier - 2 Single Click! Introduction of Weka

14 Take a tour Classifier - 3 Introduction of Weka

15 Input File:.arff Format Detail: Require @RELATION declaration associates a name with the declaration specifies the name and type of an declaration is a single line denoting the start of the data segment Introduction of Weka

16 Input File:.cvs Format Introduction of Weka

17 Output Text-based results Run Information; Summary of model; Statistics of training data; Predictions of test data; Type of sampling; Confusing Matrix; Detailed Accuracy by class; Entropy evaluation measures; … Introduction of Weka

18 Output Text-based results - example classifyResultExample.txt Introduction of Weka

19 Output Graphical-based results Introduction of Weka

20 Any questions?? Introduction of Weka


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