i have a data set of eeg recordings with 5000 rows and 59 coloumns. as coloumns are channels of eeg headsets and rows represents signal amplitude at each channel. now i used princomp to reduce the dimensions. but i am confused in variable and observation as i have a lable vector of 5000 elements to classify tha data but if i used princomp at 5000x59 i got 59x59 matrix which can't be classified by given label and if i apply command on 59x5000 data i got 5000x5000 matrix it means pca increase the dimension instead of decreasing. so kindly make me understand how can i percept variables and observation in my data.
thnx
