I didn't know this forum existed so I asked this on Stack Overflow but maybe it's more suitable here...
I have a question regarding dimensionality reduction using PCA.
If I have a train set (train.arff, 10 attributes) I perform a PCA and I save my data with respect to the new transformed variables (say I choose the two first attributes, combination of the original ones, that collect most of the variance), and call this transformed trainset "trainset-afterPCA.arff". Now I train a model using this file (which only has 2 attributes), and save it.
If now I have a new dataset, constructed with the original 10 attributes, and I want to use the model I built before to classify this new data, how do I have to proceed?
If I just try to test on this new dataset, train and test aren't compatible, right? If I ran PCA on the test set, the resulting new attributes won't be the same as the ones obtained in the training set. What should I do?
Update: Just to show (part) of the weka output:
eigenvalue proportion cumulative
2.31715 0.28964 0.28964 0.512ent-0.472Threshold+0.422impRes-0.335pssm-mut+0.28 pssm-wt...
1.72263 0.21533 0.50497 0.593pssm-mut+0.501pssm-wt+0.41 Threshold+0.403hyd+0.161sub...
1.31987 0.16498 0.66996 0.698vdw+0.628sub+0.219Threshold-0.168hyd+0.154ent...
0.88362 0.11045 0.78041 0.53impRes-0.51pssm-wt-0.478ent+0.346hyd+0.33 subs-score...
0.8404 0.10505 0.88546 0.605hyd-0.552impRes-0.319pssm-wt-0.26pssm-mut+0.235ent...
0.56935 0.07117 0.95663 -0.656vdw+0.531sub-0.449hy+0.207Threshold-0.145pssm-mut...
Eigenvectors
V1 V2 V3 V4 V5 V6
-0.4716 0.4104 0.219 -0.0231 0.215 0.2071 Threshold
-0.153 -0.1263 0.6977 0.0049 -0.1865 -0.6556 vdw
0.2465 0.4028 -0.1679 0.346 0.6055 -0.4486 hyd
0.2511 0.1609 0.6277 0.3299 0.1513 0.5306 sub
0.2799 0.5007 0.0529 -0.5097 -0.3189 0.061 pssm-wt
-0.335 0.593 -0.1004 0.0423 -0.2602 -0.145 pssm-mut
0.5118 0.0616 0.1544 -0.4783 0.2354 -0.1246 ent
0.4217 0.1459 -0.0799 0.5297 -0.5521 -0.0645 impRes
So, based on your answer, if now I choose V1 and V2 to represent my data, I have to use V1 and V2 and calculate the new attributes for the test set, previous to upload the test set to the model..
V1 --> new att 1 = 0.512ent-0.472Threshold+0.422impRes-0.335pssm-mut+0.28pssm-wt...
V2 --> new att 2 = 0.593pssm-mut+0.501pssm-wt+0.41Threshold+0.403hyd+0.161sub...