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README.md

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Updated README.md
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Ethan Smith-Coss 2025-05-30 23:51:17 +01:00
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@ -10,7 +10,7 @@ expressions:
$$ $$
\mathbf{Y} = \mathbb{KLT}\{\mathbf{X}\}, \mathbf{Y} = \mathbb{KLT}\{\mathbf{X}\},
C = \frac{1}{n-1}\mathbf{X}*\mathbf{X}, C = \frac{1}{n-1}\mathbf{X}*\mathbf{X},
\mathbf{V}^{-1}\matbf{C}\mathbf{V} = \mathbf{D}, \mathbf{V}^{-1}\mathbf{C}\mathbf{V} = \mathbf{D},
\mathit{W} \subset \mathit{V}, \mathit{W} \subset \mathit{V},
T = \mathbf{B} \cdot \mathbf{W}. T = \mathbf{B} \cdot \mathbf{W}.
$$ $$
@ -20,5 +20,8 @@ $\mathit{W}$ which is a subset of eigenvectors, explicitly or intuitively
selected. Matrix $\mathbf{T}$ is the newly reduced data with an explained selected. Matrix $\mathbf{T}$ is the newly reduced data with an explained
variance ratio $\lt1.0$, though typically very high. variance ratio $\lt1.0$, though typically very high.
For further information, or if the $\LaTeX$ does not render properly or in full,
see [Principal Component Analysis](https://en.wikipedia.org/wiki/Principal_component_analysis#Computation_using_the_covariance_method)
The source code is built entirely on the GNU GSL (2.7) library, to The source code is built entirely on the GNU GSL (2.7) library, to
utilise BLAS optimised functionality. utilise BLAS optimised functionality.