6533b85dfe1ef96bd12bdc97
RESEARCH PRODUCT
Feature Selection Approach based on Mutual Information and Partial Least Squares
Li Jie ZhaoJian TangQiang Shisubject
Variable (computer science)Threshold limit valuebusiness.industryPartial least squares regressionGeneral EngineeringPattern recognitionFeature selectionHigh dimensionalArtificial intelligenceMutual informationSpectral databusinessMathematicsdescription
Feature selection technology can improve the modeling accuracy and reduce model’s complexity, especially for the high dimensional spectral data. Aim at this problem, feature selection approach based on mutual information (MI) and partial least square (PLS) is proposed in this paper. MI values between features and responsible variable are calculated, and the threshold value using to select final features is optimal selected based on PLS algorithm. The numbers of the latent values of the PLS and the threshold value of MI are selected according the modeling performance simultaneously. The experimental results based on the near-infrared spectrum show that the proposed approach has better performance.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2014-02-27 | Advanced Materials Research |