?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=Naive+Bayes+vs.+Decision+Trees+vs.+Neural+Networks+in+the+Classification+of+Training+Web+Pages&rft.creator=XHEMALI%2C+Daniela+&rft.creator=J.+HINDE%2C+Christopher+&rft.creator=G.+STONE%2C+Roger+&rft.subject=Neural+Nets&rft.description=Web+classification+has+been+attempted+through+many+different+technologies.+In+this+study+we+concentrate+on+the+comparison+of+Neural+Networks+(NN)%2C+Na%C3%AFve+Bayes+(NB)+and+Decision+Tree+(DT)+classifiers+for+the+automatic+analysis+and+classification+of+attribute+data+from+training+course+web+pages.+We+introduce+an+enhanced+NB+classifier+and+run+the+same+data+sample+through+the+DT+and+NN+classifiers+to+determine+the+success+rate+of+our+classifier+in+the+training+courses+domain.+This+research+shows+that+our+enhanced+NB+classifier+not+only+outperforms+the+traditional+NB+classifier%2C+but+also+performs+similarly+as+good%2C+if+not+better%2C+than+some+more+popular%2C+rival+techniques.+This+paper+also+shows+that%2C+overall%2C+our+NB+classifier+is+the+best+choice+for+the+training+courses+domain%2C+achieving+an+impressive+F-Measure+value+of+over+97%25%2C+despite+it+being+trained+with+fewer+samples+than+any+of+the+classification+systems+we+have+encountered.&rft.publisher=International+Journal+of+Computer+Science+Issues%2C+IJCSI&rft.date=2009-09&rft.type=Journal+(Paginated)&rft.type=PeerReviewed&rft.format=application%2Fpdf&rft.identifier=http%3A%2F%2Fcogprints.org%2F6708%2F1%2F4-1-16-23.pdf&rft.identifier=++XHEMALI%2C+Daniela++and+J.+HINDE%2C+Christopher++and+G.+STONE%2C+Roger+++(2009)+Naive+Bayes+vs.+Decision+Trees+vs.+Neural+Networks+in+the+Classification+of+Training+Web+Pages.++%5BJournal+(Paginated)%5D+++++&rft.relation=http%3A%2F%2Fcogprints.org%2F6708%2F