نتایج جستجو برای: principal component analysis

تعداد نتایج: 3331272  

Journal: :Pattern Recognition 2018
Ajay Gupta Adrian Barbu

When modeling multivariate data, one might have an extra parameter of contextual information that could be used to treat some observations as more similar to others. For example, images of faces can vary by age, and one would expect the face of a 40 year old to be more similar to the face of a 30 year old than to a baby face. We introduce a novel manifold approximation method, parameterized pri...

2017
James Worrell

Principal components analysis (PCA) is a dimensionality reduction technique that can be used to give a compact representation of data while minimising information loss. Suppose we are given a set of data, represented as vectors in a high-dimensional space. It may be that many of the variables are correlated and that the data closely fits a lower dimensional linear manifold. In this case, PCA fi...

2012
Fang Han Han Liu

We propose two new principal component analysis methods in this paper utilizing a semiparametric model. The according methods are named Copula Component Analysis (COCA) and Copula PCA. The semiparametric model assumes that, after unspecified marginally monotone transformations, the distributions are multivariate Gaussian. The COCA and Copula PCA accordingly estimate the leading eigenvectors of ...

Journal: :CoRR 2014
Pengtao Xie Eric P. Xing

Principal Component Analysis (PCA) aims to learn compact and informative representations for data and has wide applications in machine learning, text mining and computer vision. Classical PCA based on a Gaussian noise model is fragile to noise of large magnitude. Laplace noise assumption based PCA methods cannot deal with dense noise effectively. In this paper, we propose Cauchy Principal Compo...

Journal: :Physical review 2021

Principal component analysis (PCA) has been applied to analyze random fields in various scientific disciplines. However, the explainability of PCA remains elusive unless strong domain-specific knowledge is available. This paper provides a theoretical framework that builds duality between eigenmodes field and eigenstates Schr\"odinger equation. Based on we propose algorithm replace expensive sol...

Journal: :journal of paramedical sciences 0
mahdieh khalili department of biostatistics, faculty of paramedical sciences, shahidbeheshti university of medical sciences, tehran, iran hamid alavi majd department of biostatistics, faculty of paramedical sciences, shahidbeheshti university of medical sciences, tehran, iran soheila khodakarim department of biostatistics, faculty of paramedical sciences, shahidbeheshti university of medical sciences, tehran, iran batool ahadi mohsen hamidpour department of hematology, faculty of paramedical sciences, shahidbeheshti university of medical sciences, tehran, iran

the aim of this study was to propose a method for improving the power of recognition and classification of thromboembolic syndrome based on the analysis of ‎ gene expression data using artificial neural networks. the studied method was performed on a dataset which contained data about 117 patients admitted to a hospital in durham in 2009. of all the studied patients, 66 patients were suffering ...

Journal: :journal of mining and environment 2015
h. shahi r. ghavami riabi a. kamkar ruhani h. asadi haroni

in this research work, the frequency domain (fd) of surface geochemical data was analyzed to decompose the complex geochemical patterns related to different depths of the mineral deposit. in order to predict the variation in mineralization in the depth and identify the deep geochemical anomalies and blind mineralization using the surface geochemical data for the dalli cu-au porphyry deposit, a ...

Journal: :the modares journal of electrical engineering 2015
hamid reza shahdoosti hesan ghassemian

an ideal fusion method preserves the spectral information in fused image without spatial distortion. the pca is believed to be a well-known pan-sharpening approach and being widely used for its efficiency and high spatial resolution. however, it can distort the spectral characteristics of multispectral images. the current paper tries to present a new fusion method based on the same concept. in ...

Journal: :journal of agricultural science and technology 2014
m. mathur

spatial patterns are useful descriptors of the horizontal structure in a plant population and may change over time as the individual components of the population grow or die out. but, whether this is the case for desert woody annuals is largely unknown. in the present investigation, the variations in spatial patterns of tribulus terrestris during different pulse events in semi-arid area of the ...

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