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A Partial Least Squares based algorithm for parsimonious variable selection
... where the response y was permuted at random. From this the upper 0.1% percentile of the null-distribution is determined, which is approximately corresponds to the selectivity score above 0.01. For each phylum and vari- ... See full document
12
A Robust Collaborative Recommendation Algorithm Based on Least Median Squares Estimator
... is based on the calculation of users’ conditional probability under different latent ...the variable selection method based on principal component analysis is proposed to detect and eliminate ... See full document
7
An Objective Wavelength Selection Method Based on Moving Window Partial Least Squares for Near-Infrared Spectroscopy
... According to the new method, Fig.6 shows wavelength indicator line of corn dataset. Fig.7 depicts the RMSECV change line which displays a similar characteristic with Fig.3 in general terms, that is to say, RMSECV curve ... See full document
7
Analysis of TCM Data Based on Partial Least Squares within Random Forest
... extraction algorithm based on AutoEncoder is proposed, the results show it can get features well representative the ...the algorithm requires large-scale training data, TCM data is usually small ... See full document
8
Analysis of partial least squares algorithm based on SBM DEA
... the partial least squares (PLS) is able to recognize the noise, however, it fails to analyze the noise in the multidimensional ...) algorithm to optimize ...data based on the ...SBM ... See full document
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Automatic determination of optimal spectral peaks for classification of Chinese tea varieties using laser-induced breakdown spectroscopy
... uninformative variable elimination (UVE) and partial least squares projection algorithm were used to obtain the optimal LIBS spectral features of tea ...for variable ... See full document
5
Lee07c
... of partial least squares when building the calibration model for a quantitative phase analysis based on X-ray diffraction ...a variable selection procedure to reduce the ... See full document
6
Rapid detection of total nitrogen content in soy sauce using NIR spectroscopy
... using partial least squares (PLS) regression with ...and variable selection was done by Costa Pereira et ...interval partial least square (Si-PLS) algorithm was ... See full document
6
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... and partial least squares (PLS) were used to derive the QSAR equations and feature selection was performed by the use of genetic algorithm ...for variable selection ... See full document
16
Comparison of a Genetic Algorithm Variable Selection and Interval Partial Least Squares for quantitative analysis of lactate in PBS
... wavelength selection for the development of accurate, robust, and interpretable predictive models have been highlighted in the ...genetic algorithm-based wavelength selection and two interval ... See full document
5
Predicting bruise susceptibility in apples using Vis/SWNIR technique combined with ensemble learning
... i.e. partial least squares model (PLS), partial least squares model combined with successful projection algorithm (SPA-PLS), and selective ensemble learning based ... See full document
10
Parsimonious least squares support vector regression using orthogonal forward selection with the generalised kernel model
... parameters based on the given training data before doing a classical LS-SVM ...forward selection procedure is adopted to append regressors one by one by incrementally minimising the regularised training ... See full document
12
Complete Least Squares: A New Variable Screening and Selection Method.
... Figure 4.4 presents the mean Precision-Recall curve for each method. The Precision- Recall curve indicates how a variable selection algorithm based on these orderings would perform. Curves ... See full document
173
An Optimized BP Algorithm Based on PLS
... BP algorithm is powerless, when in the face of singular sample data, which with high characteristic dimensional and small sample ...network algorithm based on the partial least ... See full document
5
Predicting the quality of ryegrass using hyperspectral imaging
... WSC were determined by liquid/gas chromatog- raphy–mass spectrometry based technique [35]. Dry matter and Ash/OM were determined by AOAC 930.15/925.10/942.05. For Ash determination the sam- ple was ignited at 500 ... See full document
12
Partial Least Squares in Constructing Candidates Model Averaging Muhammad Arna Ramadhan, Bagus Sartono, Anang Kurnia
... There are three main steps in PLSMA method. First step, half of data is used to estimate the parameters for each candidate model. In the second step, determine AIC weights for each candidate model. The third step, the ... See full document
5
“Data Mining techniques differentiation between NPPLS and PLS”
... with variable 8 being the output variable and the rest being input ...the Partial Least Square model and that of the Nonlinear Partial Least ... See full document
12
NEW MODEL TRANSFORMATION USING REQUIREMENT TRACEBILITY FROM REQUIREMENT TO UML BEHAVIORAL DESIGN
... Network parallel computing environments to achieve parallel algorithm requires minimizing the communication overhead, and using the medium- grained task parallelism. To this end, according to the inherent ... See full document
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Some aspects of progeny testing Southdown rams : a thesis presented in part fulfilment of the requirements for the degree of Master of Agricultural Science in Massey University of Manawatu, New Zealand
... Least squares means, least squares deviations of sire groups from the means, least squares differences due to birthrank and sex, and partial regression coefficients for the characteristi[r] ... See full document
14
Particle swarm optimized partial least square support vector regression model for tax revenue prediction
... PSO algorithm is to initialize a stochastic particles (stochastic solution) and then search for the optimal solution through the ...optimization algorithm for the parameter optimization process can be ... See full document
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