Selection of Mulberry Genotypes for Rainfed Conditions through Principal Component Analysis
نویسندگان
چکیده
منابع مشابه
Conditions for Robust Principal Component Analysis
Principal Component Analysis (PCA) is the problem of finding a lowrank approximation to a matrix. It is a central problem in statistics, but it is sensitive to sparse errors with large magnitudes. Robust PCA addresses this problem by decomposing a matrix into the sum of a low-rank matrix and a sparse matrix, thereby separating out the sparse errors. This paper provides a background in robust PC...
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Principal component analysis (PCA) is a popular dimension reduction method that approximates a numerical data matrix by seeking principal components (PC), i.e. linear combinations of variables that captures maximal variance. Since each PC is a linear combination of all variables of a data set, interpretation of the PCs can be difficult, especially in high-dimensional data. In order to find ’spa...
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ژورنال
عنوان ژورنال: International Journal of Current Microbiology and Applied Sciences
سال: 2021
ISSN: 2319-7692,2319-7706
DOI: 10.20546/ijcmas.2021.1001.320