Antitubercular activity of Sulfathiazole Derivitives series were subjected to Quantitative Structure Activity Relationship (QSAR) Analysis with an attempt to derive and understand a correlation between the Biologically Activity as dependent variable and various descriptors as independent variables. QSAR models generated using 28 compounds. Several statistical regression expressions were obtaine...

This paper presented a novel method named wavelet packet transform-based partial least squares method (WPTPLS) for simultaneous spectrophotometric determination of alpha-naphthylamine, p-nitroaniline, and benzidine. Wavelet packet representations of signals provided a local time-frequency description and separation ability between information and noise. The quality of the noise removal can be i...

Speaker recognition systems have been shown to work well when recordings are collected in conditions with relatively limited mismatch. Thus, a significant focus of the current research is techniques for robust system performance when greater variability is present. This study considers a diverse data set with recordings collected in multiple different rooms with different types of microphones. ...

Genomic selection involves computing a prediction equation from the estimated effects of a large number of DNA markers based on a limited number of genotyped animals with phenotypes. The number of observations is much smaller than the number of independent variables, and the challenge is to find methods that perform well in this context. Partial least squares regression (PLS) and sparse PLS wer...

0019-1035/$ see front matter Published by Elsevier http://dx.doi.org/10.1016/j.icarus.2012.07.023 ⇑ Corresponding author at: Department of Earth S Purdue University Indianapolis, IN 46202, United Stat E-mail addresses: [email protected], njushuaili@ The goal of this study is to develop an efficient and accurate model for using visible–near infrared reflectance spectra to estimate the abundance...

This work provides a novel derivation based on optimization for the partial least squares (PLS) algorithm for linear regression and the kernel partial least squares (K-PLS) algorithm for nonlinear regression. This derivation makes the PLS algorithm, popularly and successfully used for chemometrics applications, more accessible to machine learning researchers. The work introduces Direct K-PLS, a...