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Data Mining: A Preprocessing Engine

2006; Science Publications; Volume: 2; Issue: 9 Linguagem: Inglês

10.3844/jcssp.2006.735.739

1552-6607

Luai Al-Shalabi, Zyad Shaaban, Basel Kasasbeh,

Neural Networks and Applications

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 new matrix was designed to check for the best normalization method based on the factors and their priorities. Recommendations were concluded.