Principal component analysis (PCA) has been successfully applied in structural dynamics in recent years. However, it is usually used as a black-box, resulting in a gap between the application aspect and the physics essence of the problem. Thus a physical interpretation of PCA is necessary, ...
59 国际基础科学大会-A comparative lattice analysis of S U ( 2 ) SU(2) dark glueball 1:02:13 国际基础科学大会-Equiangular lines and eigenvalue multiplicity-Yufei Zhao 55:33 国际基础科学大会-Nahm Transform: Old and New-Mark Stern 58:16 国际基础科学大会-Prediction of Multi-Class Peptides by...
Parallel Analysis: a method for determining significant principal components Numerous ecological studies use Principal Components Analysis (PCA) for exploratory analysis and data reduction. Determination of the number of components ... SB Franklin,DJ Gibson,PA Robertson,... - 《Journal of Vegetation Sci...
For any partial combinatory algebra (PCA for short) A, the class of A-representable partial functions from N to A quotiented by the filter of cofinite sets of N is a PCA such that the representable partial functions are exactly the limiting partial functions of A-representable partial function...
Principle components analysis (PCA) and sample histograms were checked as a part of quality control analyses of the data. Mixed-model multi-way ANOVA (which allows more than one ANOVA factor to be entered in each model) was used to compare the individual gene expression data across different ...
为了获得 :共有的(common traits),像素级别的,主要特征(这里的特征对应的是superpixels)(这些特征可能是组合的: the best combination of superpixels), 本文提出了一个语义解释框架,使用了 row-centered principal component analysis (PCA) by a genetic algorithm (遗传算法,应该是用来做pca的迭代) ...
Principal component analysisOverexploitationWest Thessaly basinGeostatisticsThe scope of this work is to elucidate the use of principal components analysis (PCA) as a tool to interpret the areal distribution of various types of ground water level fluctuation patterns within......
This representation permits equivalent, or better, classification accuracies than either principal component analysis (PCA) or multi-dimensional scaling (MDS). In the training phase, the peaks in each trace are detected and clustered in order to compile a common dictionary, which could be ...
Principal component analysis (PCA) Partial least squares discriminant analysis (PLS-DA) Hierarchical cluster analysis (HCA) / heatmaps Analysis on demand:additional statistical analyses can be performed upon request for each project. Metabolite sums and ratios: exclusively for samples measured with the...
The preparation consists of verifying the absence of interlaboratory and intralaboratory bias between measurements, centred log-ratio transformation (clr), normalisation and principal component analysis (PCA). Afterwards, the first case study indicate that the clustering separation is primarily driven by ...