Abstract
For variable selection in high dimensional spectroscopic data filter measures are in use. In the current study, majority scoring (MS) over filter mixture in Partial least squares (PLS) is introduced for variable selection. The proposed method is implemented for studying the variation in IL’s antibacterial activity against 06 microbes. MS utilizes several filter mixtures including PLS coefficients, loading weights, variable importance on projection, selectivity ratio, and significance multivariate correlation where a spectral wavelength is selected which has been scored influential by most of the above filter measures. Majority scoring in PLS (MS-PLS) identifies influential wavelength which predicts antibacterial activity against different microbes. The influential functional compounds corresponding to influential wavenumber are identified for all 06 microbes. The results indicate MV-PLS based variable (wavenumber) selection can model the spectroscopic data.
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