Text-Classification/summary at master · bharos/Text-Classification · GitHub

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Naive Bayes
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After stripping header

rec.sport.hockey: have go ca they was on hockey you it is for team he that game of and in to the
sci.med: or com have with my be edu not are this for you that it in and is of to the
soc.religion.christian: but have he for as this be are not we you it god in is and that of to the
talk.religion.misc: god he sandvik have as com for this be are not it you in is that and to of the
len =  723
0.777316735823
0.679464907261

After stop-word remove, stemming

0.777316735823
0.669718154377


SVM
-----
After stripping header

0.890733056708
0.864481248502

rec.sport.hockey: gm stats cup montreal ice leafs win playoff teams player season go games nhl play ca players game team hockey
sci.med: com pitt needles pain it dyer geb health cancer banks medicine food gordon information patients treatment medical msg disease doctor
soc.religion.christian: christian heaven geneva resurrection faith book bible christians easter our we christianity clh christ athos 1993 apr church god rutgers
talk.religion.misc: article tyre values newton weiss apple tony amorc bull moral fbi convenient order frank kent brian sandvik koresh morality objective


After stop-word remove, stemming

rec.sport.hockey: gm stats cup montreal ice leafs win playoff teams player season go games nhl play ca players game team hockey
sci.med: com pitt needles pain it dyer geb health cancer banks medicine food gordon information patients treatment medical msg disease doctor
soc.religion.christian: christian heaven geneva resurrection faith book bible christians easter our we christianity clh christ athos 1993 apr church god rutgers
talk.religion.misc: article tyre values newton weiss apple tony amorc bull moral fbi convenient order frank kent brian sandvik koresh morality objective