Rotate PCA's

Berettar

Hi there,

i am currently working on some stuff, where i want to reduce a given number of attributes to a much smaller set. So i started with a pca and a correlation matrix as visualization. So far so good, now i would like to rotate and load the factors with a derivate bigger 1 ( in my case around 20 factors ), so i am able to reduce my given attributes. Maybe i am just blind, but till now, i haven't found a proper setup to do this, any help is highly appreciated.

Greets

land

Hi,
what exactly do you mean by rotate? It seems to me, I'm not familiar with this. Where do the derivates come from?

Greetings,
  Sebastian

Berettar

Hi Sebastian,

well this is a well known method ( in german "exploratorische Faktorenanalyse" ). First you start with a datamatrix (  here the dataset ) . Upon which you get a correlation matrix - correlation of each attributes. With the correlation matrix you get a factor charged  matrix. Within PCA ( in rapidminer ) i come up to this point ( a matrix, where all attributes are loaded on the selected factors ). But then you need to rotate the factor charged matrix, so you "load" a attribute as high as possible on one factor. I know that in SPSS there is a way to do this, but i don t have SPSS, so i tried rapidminer, but can t find the rotation of the factor charged matrix.

Due to the fact that i am on work, i don t have my rapidminer setup visible, but  as far as i remember following setup should fit mine:

ExcelExampleSet

PCA

Correlation Matrix ( Visualization )


Greetings from Germany

p.s: derivates are given by PCA in rapidminer

[edit] Rotation should be something like the VARIMAX or QUARTIMAX algorithm

land

Hi,
currently neither the Varimax or Quartimax algorithm is available, but I added it on the agenda. We are going to enlarge the functionality in this area with the next versions.

Greetings,
  Sebastian