Search for tag: "pca"

ML3: Dimensionality Reduction using Principal Component Analysis

In this video, we will learn that we can use Principal Component Analysis (PCA) to find a transformation matrix that minimises reconstruction error for dimensionality reduction. We also show how this…

From  Elliot Crowley on November 5th, 2020 0 likes 16 plays 0  

MLP Lecture 06 - Clip 03 - Data Normalisation

Machine Learning Practical (MLP) Lecture 06, Clip 03 / 05.

From  Pavlos Andreadis on October 24th, 2020 1 likes 203 plays 0  

Unsupervised Learning

Unsupervised Learning

From  Dimitrios Doudesis on June 8th, 2020 0 likes 85 plays 0  

Properties of eigenfaces

Properties of eigenfaces

From  Nigel Goddard on September 25th, 2016 1 likes 1,521 plays 0  

Pros and cons of dimensionality reduction

Pros and cons of dimensionality reduction

From  Nigel Goddard on September 25th, 2016 1 likes 2,109 plays 0  

Principal component analysis

Principal component analysis

From  Nigel Goddard on September 25th, 2016 1 likes 2,219 plays 0  

Linear discriminant analysis

Linear discriminant analysis

From  Nigel Goddard on September 25th, 2016 1 likes 1,632 plays 0  

Classification with PCA features

Classification with PCA features

From  Nigel Goddard on September 25th, 2016 1 likes 1,722 plays 0  

When principal components fail

When principal components fail

From  Nigel Goddard on September 25th, 2016 1 likes 1,640 plays 0  

Eigenface representation

Eigenface representation

From  Nigel Goddard on September 25th, 2016 1 likes 1,730 plays 0  

Eigen-faces

Eigen-faces

From  Nigel Goddard on September 25th, 2016 1 likes 1,920 plays 0  

Principal component analysis for the impatient

Principal component analysis for the impatient

From  Nigel Goddard on September 25th, 2016 1 likes 1,766 plays 0  

How many principal components to use

How many principal components to use

From  Nigel Goddard on September 25th, 2016 1 likes 1,745 plays 0  

Eigenvalue = variance along eigenvector

Eigenvalue = variance along eigenvector

From  Nigel Goddard on September 25th, 2016 1 likes 1,785 plays 0  

Eigenvector = direction of maximum variance

Eigenvector = direction of maximum variance

From  Nigel Goddard on September 25th, 2016 2 likes 2,223 plays 0  

Low-dimensional projections of data

Low-dimensional projections of data

From  Nigel Goddard on September 25th, 2016 0 likes 2,089 plays 0