Based on k-Medoids and c5.0 Joint Constraint of the Drug Information Mining Algorithm

Hui Zhang

doi:10.4028/www.scientific.net/AMM.397-400.2291

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 397-400Based on k-Medoids and c5.0 Joint Constraint of...

Based on k-Medoids and c5.0 Joint Constraint of the Drug Information Mining Algorithm

Abstract:

When the mass data information for drug contains no real or noise effects of information, the general data mining analysis method will have a great advantage, the traditional medicine association behavior is used in the analysis of a categories data mining analysis method, ignore drug data analysis results and the practical next behavior prediction contact. In order to solve the problem put forward the k-medoids and c5.0 joint constraints drug data mining methods, and in the first step of clustering analysis of fully considering the effect of noise and isolated points, with the first step clustering results were late to the classification of the decision tree as data sample, and the appropriate data pretreatment, so it can guarantee the accuracy of the calculation model. Experiments prove this drug data analysis models are available, the mining efficiency is higher.

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Periodical:

Applied Mechanics and Materials (Volumes 397-400)

Pages:

2291-2295

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.397-400.2291

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Online since:

September 2013

Authors:

Hui Zhang

Keywords:

Combined Constraints, Data Mining (DM), Data Pre-Processing

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