Normalization as a Preprocessing Engine for Data Mining and the Approach of Preference Matrix

Luai Al Shalabi; Zyad Shaaban

doi:10.1109/DEPCOS-RELCOMEX.2006.38

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Conference proceeding

Normalization as a Preprocessing Engine for Data Mining and the Approach of Preference Matrix

Luai Al Shalabi and Zyad Shaaban

2006 International Conference on Dependability of Computer Systems, pp.207-214

05/2006

DOI: https://doi.org/10.1109/DEPCOS-RELCOMEX.2006.38

Abstract

Classification algorithms

Clustering algorithms

Data analysis

Data mining

Databases

Decision trees

Engines

Nearest neighbor searches

Neural networks

Redundancy

This study is emphasized on different types of normalization. Each of which was tested against the ID3 methodology using the HSV data set. Number of leaf nodes, accuracy, and tree growing time are three factors that were taken into account. Comparisons between different learning methods were accomplished as they were applied to each normalization method. A simple matrix was designed to check for the best normalization method based on the factors and their priorities. Recommendations were concluded

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Details

Title: Normalization as a Preprocessing Engine for Data Mining and the Approach of Preference Matrix
Creators - without role: Luai Al Shalabi - Applied Science Private University
Zyad Shaaban - Applied Science Private University
Publication Details: 2006 International Conference on Dependability of Computer Systems, pp.207-214
Publisher: IEEE
Identifiers: 9933759808331
Academic Unit: University of Tabuk
Language: English
Resource Type: Conference proceeding