PCA_4perPage - Outline Principal Components Analysis 1...

Info iconThis preview shows pages 1–3. Sign up to view the full content.

View Full Document Right Arrow Icon
Principal Components Analysis Data Mining Prof. Dawn Woodard School of ORIE Cornell University 1 Outline 1 Announcements 2 PCA 2 Announcements Questions? 4 Principal Components Figures from Shmueli, Patel, and Bruce (2007): 6
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This data set contains nutritional and consumer rating data on cereals: 7 Principal Components There are 77 cereals total in the data set. 8 Principal Components There are 15 variables in the data set: 9 Principal Components 12 of the 15 variables are continuous. We wish to summarize the 12 continuous attributes with just a few variables that are linear combinations of those attributes We want these few variables to capture the original structure of the data as closely as possible For instance, we want the cereals that are close to each other in the original 12-dimensional space to be close to each other in the new low-dimensional space. .. and we want the cereals that are far apart in the original space to still be far apart. 10
Background image of page 2
Image of page 3
This is the end of the preview. Sign up to access the rest of the document.

Page1 / 8

PCA_4perPage - Outline Principal Components Analysis 1...

This preview shows document pages 1 - 3. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online