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  2. 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.

  3. 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.

  4. 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.

  5. Students will ‘see the legacy of the Gullah.’ Charter school ...

    www.aol.com/news/students-see-legacy-gullah...

    In Beaufort County public schools, 85.7% of African American students graduate compared to 91.5% of Caucasian students and 88.5% of all students.Statewide, the graduation rates are worse for each ...

  6. 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.

  7. Robust principal component analysis - Wikipedia

    en.wikipedia.org/wiki/Robust_principal_component...

    The 2014 guaranteed algorithm for the robust PCA problem (with the input matrix being = +) is an alternating minimization type algorithm. [12] The computational complexity is (⁡) where the input is the superposition of a low-rank (of rank ) and a sparse matrix of dimension and is the desired accuracy of the recovered solution, i.e., ‖ ^ ‖ where is the true low-rank component and ^ is the ...

  8. Helena Public School District - Wikipedia

    en.wikipedia.org/wiki/Helena_Public_School_District

    Helena Public Schools is a public school district located in Helena, Montana, United States. [2] It has two components: Helena Elementary School District and Helena High School District. [3] [4] The National Center for Education Statistics (NCES) code for the elementary district, which covers grades Pre-Kindergarten to 8, is 3000005. [5]

  9. Active learning (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Active_learning_(machine...

    This type of iterative supervised learning is called active learning. Since the learner chooses the examples, the number of examples to learn a concept can often be much lower than the number required in normal supervised learning. With this approach, there is a risk that the algorithm is overwhelmed by uninformative examples.