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⚙️AlgorithmIntermediate

Principal Component Analysis (PCA)

Principal Component Analysis (PCA) finds new orthogonal axes (principal components) that capture the maximum variance in your data.

#principal component analysis#pca c++#eigendecomposition+11
∑MathIntermediate

Multivariate Gaussian Distribution

A multivariate Gaussian (normal) distribution models a vector of real-valued variables with a bell-shaped probability hill in many dimensions.

#multivariate normal
Advanced
Filtering by:
#covariance matrix
#gaussian distribution
#covariance matrix
+11
∑MathIntermediate

Positive Definite Matrices

A real symmetric matrix A is positive definite if and only if x^T A x > 0 for every nonzero vector x, and positive semidefinite if x^T A x ≥ 0.

#positive definite#positive semidefinite#cholesky decomposition+11
∑MathIntermediate

Variance and Covariance

Variance measures how spread out a random variable is around its mean, while covariance measures how two variables move together.

#variance#covariance#standard deviation+12