Non-invasive blood glucose measurement has attracted much attention in recent years. Near-infrared (NIR) spectroscopy is currently used for frequent detection of blood glucose levels. The dynamic spectrum (DS) method, which can eliminate the individual discrepancy, is the development of ordinary NIR spectroscopy. Classic Least Squares (CLS) is usually employed to analyze the spectra. In this wo...

Inhibitory activity against aldose reductase enzyme of nineteen flavonoid derivatives was subjected to classical quantitative structure activity relationship (QSAR) analysis using electrotopological state (E-state) atom parameter. For the development of the QSAR models, statistical techniques like stepwise multiple linear regression and partial least squares (PLS) were used. The best equation i...

Microarray data usually contain missing values, thus estimating these missing values is an important preprocessing step. This paper proposes an estimation method of missing values based on Partial Least Squares (PLS) regression. The method is feasible for microarray data, because of the characteristics of PLS regression. We compared our method with three methods, including ROWaverage, KNNimpute...

Abbreviations 3D D three-dimensional; C D molar concentration of a drug; CBG D corticosteroid binding globulin; CoMFA D comparative molecular field analysis; CoMSIA D comparative molecular similarity indices analysis; GOLPE D generating optimal linear PLS estimations; PLS D partial least squares; PRESS D predictive residual sum of squares; RMS D root mean squares; TBG D testosterone binding glo...

Building classification models plays an important role in DNA mircroarray data analyses. An essential feature of DNA microarray data sets is that the number of input variables (genes) is far greater than the number of samples. As such, most classification schemes employ variable selection or feature selection methods to pre-process DNA microarray data. This paper investigates various aspects of...

Partial Least Squares (PLS) is a statistical technique that is widely used in the Partial Least Squares (PLS) is a popular technique for estimating structural equation models with latent variables. It is frequently perceived as an alternative to covariance analysis of such models. While its proponents recognize the shortcomings of PLS for testing explanatory models in comparison to covariance m...

in the present work we study the use of fourier transform near infrared spectroscopy (ftnirs)technique to analysis the calcium (ca), phosphorus (p) and copper (cu) contents offish meal. the regression methods employed were partial least squares (pls) and kernelpartial least squares (kpls). the results showed that the efficiency of kpls was better thanpls. as a whole, the application of ft-nirs ...