Fuzzy Systems

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Comprehensive Feature Selection for Clinical Dataset


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1 Sri Ramakrishna College of Arts and Science College for Women, Coimbatore - 641044, India
     

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Feature selection plays a significant role in any data mining research problem. In this research work, comprehensive feature selection is applied for selecting the attributes in the chosen PIMA Indian diabetes dataset. The comprehensive feature selection mechanism makes use of maximum significance pattern for selecting the most edifying features, which effectively distinguish between different classes of samples.

Keywords

Feature Selection, Data Mining, Gestational Diabetes, Accuracy, Time Taken, Feature Selection, Risk Prediction.
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  • Comprehensive Feature Selection for Clinical Dataset

Abstract Views: 249  |  PDF Views: 2

Authors

S. Kavipriya
Sri Ramakrishna College of Arts and Science College for Women, Coimbatore - 641044, India
T. Deepa
Sri Ramakrishna College of Arts and Science College for Women, Coimbatore - 641044, India

Abstract


Feature selection plays a significant role in any data mining research problem. In this research work, comprehensive feature selection is applied for selecting the attributes in the chosen PIMA Indian diabetes dataset. The comprehensive feature selection mechanism makes use of maximum significance pattern for selecting the most edifying features, which effectively distinguish between different classes of samples.

Keywords


Feature Selection, Data Mining, Gestational Diabetes, Accuracy, Time Taken, Feature Selection, Risk Prediction.

References