Difference between revisions of "Principal Component Analysis"
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(Created page with "'''Principal Component Analysis''' is the method that calculates the set of axis whose vector distribution is larger (main axis) from set of vector whose consist of multivaria...") |
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| − | '''Principal Component Analysis''' is the method that calculates | + | '''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 |
| + | whose vector distribution is larger (main axis) from set of vector whose consist of multivariates to Multivariate Axis (Multivariate Space). | ||
[[File:Fig-PCA.png]] | [[File:Fig-PCA.png]] | ||
Revision as of 08:00, 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 whose vector distribution is larger (main axis) from set of vector whose consist of multivariates to Multivariate Axis (Multivariate Space).
