Discriminative approaches ( especially SVMs ) have been shown to be very effective for many supervised classification tasks ; see , for example , ( Joachims , 1998 ; Ng and Jordan , 2001 ) .
text categorization with support vector machines learning with many relevant features
Thorsten Joachims
Although our results were not obtained from the same exact collection as those used by authors of these two previous studies , comparable experiments suggest that our techniques are competitive in terms of performance , and may offer additional advantages as well . Discriminative approaches ( especially SVMs ) have been shown to be very effective for many supervised classification tasks ; see , for example , ( Joachims , 1998 ; Ng and Jordan , 2001 ) . However , their high computational complexity ( quadratic in the number of training samples ) renders them prohibitive for massive data processing .
Discriminative approaches ( especially SVMs ) have been shown to be very effective for many supervised classification tasks ; see , for example , ( @@CITATION ; Ng and Jordan , 2001 ) .