Search for tag: "pca"

Unsupervised Learning

Unsupervised Learning

From  Dimitrios Doudesis on June 8th, 2020 0 likes 77 plays 0  

Properties of eigenfaces

Properties of eigenfaces

From  Nigel Goddard on September 25th, 2016 1 likes 1,033 plays 0  

Pros and cons of dimensionality reduction

Pros and cons of dimensionality reduction

From  Nigel Goddard on September 25th, 2016 1 likes 1,566 plays 0  

Principal component analysis

Principal component analysis

From  Nigel Goddard on September 25th, 2016 1 likes 1,577 plays 0  

Linear discriminant analysis

Linear discriminant analysis

From  Nigel Goddard on September 25th, 2016 1 likes 1,172 plays 0  

Classification with PCA features

Classification with PCA features

From  Nigel Goddard on September 25th, 2016 1 likes 1,214 plays 0  

When principal components fail

When principal components fail

From  Nigel Goddard on September 25th, 2016 1 likes 1,143 plays 0  

Eigenface representation

Eigenface representation

From  Nigel Goddard on September 25th, 2016 1 likes 1,133 plays 0  

Eigen-faces

Eigen-faces

From  Nigel Goddard on September 25th, 2016 1 likes 1,247 plays 0  

Principal component analysis for the impatient

Principal component analysis for the impatient

From  Nigel Goddard on September 25th, 2016 1 likes 1,234 plays 0  

How many principal components to use

How many principal components to use

From  Nigel Goddard on September 25th, 2016 1 likes 1,212 plays 0  

Eigenvalue = variance along eigenvector

Eigenvalue = variance along eigenvector

From  Nigel Goddard on September 25th, 2016 1 likes 1,245 plays 0  

Eigenvector = direction of maximum variance

Eigenvector = direction of maximum variance

From  Nigel Goddard on September 25th, 2016 2 likes 1,602 plays 0  

Low-dimensional projections of data

Low-dimensional projections of data

From  Nigel Goddard on September 25th, 2016 0 likes 1,442 plays 0  

Finding eigenvalues and eigenvectors

Finding eigenvalues and eigenvectors

From  Nigel Goddard on September 25th, 2016 1 likes 1,490 plays 0  

Principal components = eigenvectors

Principal components = eigenvectors

From  Nigel Goddard on September 25th, 2016 1 likes 1,704 plays 0