principal component analysis C#

Principal Components Regression: Part 3 – The NIPALS Algorithm

Principal Components Regression: Recap of Part 2 Recall that the least squares solution to the multiple linear problem is given by(1) $latex \hat{\beta} = (X^T X)^{-1} X^T y $ And that problems occurred finding when the matrix(2) was close to being singular. The Principal Components Regression approach to addressing the problem is to replace in equation (1) with a better conditioned...
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Principal Components Regression: Part 2 – The Problem With Linear Regression

This is the second part in a three part series on PCR, the first article on the topic can be found here. The Linear Regression Model Multiple Linear Regression (MLR) is a common approach to modeling the relationship between one or two or more explanatory variables and a response variable by fitting a linear equation to observed data. First let’s set up some notation. I will be rather brief, ass...
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Clustering Analysis, Part I: Principal Component Analysis (PCA)

Cluster analysis or clustering is the assignment of a set of observations into subsets (called clusters) so that observations in the same cluster are similar in some sense. Cluster analysis is the assignment of a set of objects into one or more clusters based on object similarity. NMath Stats includes a variety of techniques for performing cluster analysis, which we will explore in a series of p...
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