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...

Simultaneous spectrophotometric determination of Mn, Zn and Co was studied by two methods, classical partial least-squares (PLS) and kernel partial least-squares (KPLS), with 2-(5-bromo-2- pyridylazo)-5-diethylaminephenol (5-Br-PADAP) and cetyl pyridinium bromide (CPB). Two programs, SPGRPLS and SPGRKPLS, were designed to perform the calculations. Eight error functions were calculated for deduc...

This paper compares and discusses four techniques for model order reduction based on compressed sensing (CS), less relevant basis removal (LRBR), principal component analysis (PCA) and partial least squares (PLS). CS and PCA have already been used for reducing the order of power amplifier (PA) behavioral models for digital predistortion (DPD) purposes. While PLS, despite being popular in some s...

This research addressed a rapid method to monitor hardwood chemical composition by applying Fourier transform infrared (FT-IR) spectroscopy, with particular interest in model performance for interpretation and prediction. Partial least squares (PLS) and principal components regression (PCR) were chosen as the primary models for comparison. Standard laboratory chemistry methods were employed on ...

Two multivariable problems of general interest are factor analysis and regression. This paper examines partial least squares (PLS) as a tool for both problems. For single output data sets, the familiar PLS algorithm is applicable to both problems. For multiple output problems the familiar PLS algorithm 1, 2, 3] (called fact-PLS in this paper) is appropriate for factor analysis. However fact-PLS...

13 Abstract 14 Soil has been utilized in criminal investigations for some time because of its prevalence and 15 transferability. It is usually the physical characteristics that are studied, however the research 16 carried out here aims to make use of the chemical profile of soil samples. The research we are 17 presenting in this work used sieved (2mm) soil samples taken from the top soil layer ...

2 Analysis of a renal cell carcinoma (RCC) cancer dataset 1 2.1 Pre-processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.1.1 Normalization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.1.2 Resampling to unit resolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.1.3 ...

Use of the partial least squares (PLS) method has been on the rise among e-collaboration researchers. It has also seen increasing use in a wide variety of fields of research. This includes most business-related disciplines, as well as the social and health sciences. The use of the PLS method has been primarily in the context of PLS-based structural equation modeling (SEM). This article discusse...

Aiming at the problem that changes of nonlinear dynamic resistance of stator affect the performance of speed sensorless vector control system, a hybrid computing intelligence approach is used in the identification of stator resistance of motorized spindle. The partial least squares (PLS) regression is combined with neural network to solve the problem of few samples and multi-correlation of vari...

the combinations of inductively coupled plasma-optical emission spectrometry (icp-oes) and three classification algorithms, i.e., partial least squares discriminant analysis (pls-da), least squares support vector machine (ls-svm) and soft independent modeling of class analogies (simca), for discriminating different brands of iranian bottled mineral waters, were explored. icp-oes was used for th...