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  2. Multilinear principal component analysis - Wikipedia

    en.wikipedia.org/wiki/Multilinear_principal...

    Multilinear principal component analysis (MPCA) is a multilinear extension of principal component analysis (PCA) that is used to analyze M-way arrays, also informally referred to as "data tensors". M-way arrays may be modeled by linear tensor models, such as CANDECOMP/Parafac, or by multilinear tensor models, such as multilinear principal ...

  3. Principal component regression - Wikipedia

    en.wikipedia.org/wiki/Principal_component_regression

    In statistics, principal component regression (PCR) is a regression analysis technique that is based on principal component analysis (PCA). PCR is a form of reduced rank regression. [1] More specifically, PCR is used for estimating the unknown regression coefficients in a standard linear regression model.

  4. Principal component analysis - Wikipedia

    en.wikipedia.org/wiki/Principal_component_analysis

    Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing.. The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified.

  5. Kernel principal component analysis - Wikipedia

    en.wikipedia.org/wiki/Kernel_principal_component...

    Output after kernel PCA, with a Gaussian kernel. Note in particular that the first principal component is enough to distinguish the three different groups, which is impossible using only linear PCA, because linear PCA operates only in the given (in this case two-dimensional) space, in which these concentric point clouds are not linearly separable.

  6. Functional principal component analysis - Wikipedia

    en.wikipedia.org/wiki/Functional_principal...

    Functional principal component analysis (FPCA) is a statistical method for investigating the dominant modes of variation of functional data.Using this method, a random function is represented in the eigenbasis, which is an orthonormal basis of the Hilbert space L 2 that consists of the eigenfunctions of the autocovariance operator.

  7. Anderson School District Five - Wikipedia

    en.wikipedia.org/wiki/Anderson_School_District_Five

    New Prospect Elementary School [10] PK-5th 464 Malura Shady 126 New Prospect Church Rd Anderson, SC 29625 link: North Pointe Elementary School [11] PK-5th 492 Jill Brackett 3325 Highway 81N Anderson, SC 29621 link: Varennes Elementary School [12] 3rd-5th 370 Danessa Barr 1820 U.S. 29 Business Anderson, SC 29626 link: Whitehall Elementary School ...

  8. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    T. Almeida et al. Twenty Newsgroups Dataset Messages from 20 different newsgroups. None. 20,000 Text Natural language processing 1999 [42] T. Mitchell et al. Spambase Dataset Spam emails. Many text features extracted. 4,601 Text Spam detection, classification 1999 [43] M. Hopkins et al.

  9. Anderson Community School Corporation - Wikipedia

    en.wikipedia.org/wiki/Anderson_Community_School...

    Because of budget cuts, South Side Middle School, Robinson Elementary School, and others closed at the end of the 2008–2009 school year. On Tuesday, December 15, 2009, due to budget cuts, the Anderson Schools Board of Education and Interim Superintendent announced by a vote of 5 to 2 the district would be going back to one high school, one ...