Difference between revisions of "Principal Component Analysis"
From EosPedia
| Line 1: | Line 1: | ||
| − | '''Principal Component Analysis''' is the method that calculates from vector data set which has elements of Multivariate to the axis (main axis) which has maximum variance when each vector data is projected into that axis on Multivariate Space, and | + | '''Principal Component Analysis''' is the method that calculates from vector data set which has elements of Multivariate to the axis (main axis) which has maximum variance when each vector data is projected into that axis on Multivariate Space, and calculates the axis sequentially that is orthogonal(no correlation) to it and has largest variance. |
| − | + | ||
[[File:Fig-PCA.png]] | [[File:Fig-PCA.png]] | ||
Revision as of 08:06, 4 August 2014
Principal Component Analysis is the method that calculates from vector data set which has elements of Multivariate to the axis (main axis) which has maximum variance when each vector data is projected into that axis on Multivariate Space, and calculates the axis sequentially that is orthogonal(no correlation) to it and has largest variance.
