I'm trying to classify some samples in to two different classes. each sample contains several features. But the problem is these samples belong to specific groups and each feature represent some property of that specific group. generally my data looks like this:
+1 1:547.6949 3:-122.99 4:-150.7976 5:-39.5595 6:-39.31721
-1 1:165.0353 3:-108.6274 4:-155.5586 5:-25.6145 6:-24.43071
-1 1:232.7848 3:-134.1802 4:-157.5643 5:-39.3388 6:-39.202710
-1 1:299.3863 3:-125.8626 4:-150.9111 5:-49.781 6:-52.444
-1 1:161.2316 3:-120.7769 4:-167.4669 5:-26.4132 6:-26.4737
-1 1:334.6234 3:-129.6332 4:-148.9993 5:-58.6543 6:-61.318
-1 1:203.4685 3:-121.9352 4:-158.4352 5:-39.1206 6:-39.086
-1 1:206.0046 3:-126.0539 4:-158.7209 5:-41.1821 6:-43.845
-1 1:229.0727 3:-107.8596 4:-160.4539 5:-40.8166 6:-43.4803
-1 1:202.8949 3:-137.3044 4:-166.1187 5:-36.4276 6:-37.438
-1 1:361.9454 3:-88.4864 4:-160.604 5:-27.7027 6:-23.787
+1 1:491.9685 3:-98.0369 4:-155.9668 5:-37.3844 6:-33.716
-1 1:778.6312 3:-115.5249 4:-148.5153 5:-54.9574 6:-59.09651
-1 1:413.1565 3:-92.4645 4:-159.4521 5:-35.5019 6:-29.4924
-1 1:501.4577 3:-105.343 4:-156.6044 5:-39.2832 6:-43.42
-1 1:487.5412 3:-115.4553 4:-155.5021 5:-47.0739 6:-44.568
-1 1:445.5218 3:-109.6812 4:-157.8129 5:-51.4686 6:-45.212
-1 1:316.3106 3:-93.2688 4:-162.7669 5:-31.5366 6:-28.482
-1 1:284.8187 3:-95.0161 4:-154.7459 5:-37.6311 6:-25.738
-1 1:391.9559 3:-108.8012 4:-157.7027 5:-40.0802 6:-44.219
these are samples of two groups of data in each there is only one (+1) class and the rest is (-1). each group has equal size of 10 samples. My question is, how can I use a SVM classifier which considers this grouping. Or if SVM is not the best choice, what do you suggest?
