Introduction of WEKA - Florida International University
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Transcript Introduction of WEKA - Florida International University
Introduction of Weka
Florida International University
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Introduction of Weka
Outline
Introduction
Take a tour
Input & output format
Introduction of Weka
What’s 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
Weka Homepage
http://www.cs.waikato.ac.nz/ml/weka/
To download WEKA 3.6.3:
http://sourceforge.net/projects/weka/files/weka-3-6-
windows/3.6.3/weka-3-6-3.exe/download
Introduction of Weka
Installation Weka
To run:
weka-3-6-3.exe
Introduction of Weka
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
Take a tour
Getting start
Start All Programs Weka 3.6.3 Weka 3.6
Click to Start a Tour!
Introduction of Weka
Take a tour
Weka Explorer Screenshot
Load
Filter
Label Info
Feature Info
Introduction of Weka
Take a tour
Click “Open file” ;
Choose “Weka-3.6/data/*.arff ”;
Click “Open”.
Introduction of Weka
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
Take a tour
2D Visualization
Visualize
Attributes
Introduction of Weka
Take a tour
Classifier - 1
Introduction of Weka
Take a tour
Classifier - 2
Single Click!
Introduction of Weka
Take a tour
Classifier - 3
Introduction of Weka
Input File:
.arff Format
Detail:
http://www.cs.waikato.ac.nz/~ml/weka/arff.html
Require declarations of @RELATION, @ATTRIBUTE and
@DATA
@RELATION declaration associates a name with the dataset
@ATTRIBUTE declaration specifies the name and type of an attribute
@DATA declaration is a single line denoting the start of the data segment
Introduction of Weka
Input File:
.cvs Format
Introduction of Weka
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
Output
Text-based results - example
classifyResultExample.txt
Introduction of Weka
Output
Graphical-based results
Introduction of Weka
Any questions??
Introduction of Weka