## Contrast Data Mining: Methods and Applications

author: Rao Kotagiri, Department of Computer Science and Software Engineering, The University of Melbourne
published: March 12, 2008,   recorded: March 2008,   views: 759
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# Slides

0:00 Slides Contrast Data Mining: Methods and Applications Contrast data mining -What is it ? Contrast Data Mining -What is it ? Cont. What can be contrasted ? What can be contrasted ? Cont. Alternative names for contrast data mining Characteristics of contrast data mining Contrast characteristics Cont. How is contrast data mining used ? Goals of this tutorial By the end of this tutorial you will be able to … Don‟t have time to cover .. Outline of the tutorial Basic notions and univariate case Sample Feature-Class Discriminative power Example Discriminative Power Test -Wilcoxon Rank Sum Rank Sum Calculation Example Wilcoxon Rank Sum TestCont. Discriminating with attribute values Attribute/Feature Conversion Discriminating with attribute values Attribute/Feature Conversion Discriminating Attribute Values in a Data Stream Odds ratio and Risk ratio Odds and risk ratio Cont. Odds Ratio Example Relative Risk Example Pattern/Rule Based Contrasts Overview

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# Description

The ability to distinguish, differentiate and contrast between different datasets is a key objective in data mining. Such an ability can assist domain experts to understand their data, and can help in building classification models. His presentation will introduce the principal techniques for contrasting different types of data, covering the main dataset varieties such as relational, sequence, and graph forms of data, clusters, as well as data cubes. It will also focus on some important real world application areas that illustrate how mining contrasts is advantageous.