> > > But when I pass the other parameters like -type bayes -ng 3 -source hdfs > > The train options and test options has to match. You cannot train in bayes mode and test in cbayes mode
> I am not getting the expected results. > Can any one please explain me the reason behind it. > > Thanks > Regards, > Divya > > > -----Original Message----- > From: Divya [mailto:[email protected]] > Sent: Tuesday, November 23, 2010 1:40 PM > To: '[email protected]' > Subject: RE: classification example doubts > > I am following same steps > But no success... > > -----Original Message----- > From: Sreejith S [mailto:[email protected]] > Sent: Friday, November 19, 2010 4:00 PM > To: [email protected] > Subject: Re: classification example doubts > > step 1 : U can provide ur own sample data set using the prepare20news > example > just provide ur input dir.This is to perform some normalization on each > file.This is a must > > stpe2 : Train the classifier with the normalized list of files. > u get a model dir which contains the trained data set in hdfs. > > step3 : Test the classifier > By using the trained model and sample input u can test the classifier > > Regards > Sreejith > > > On Fri, Nov 19, 2010 at 1:15 PM, Divya <[email protected]> wrote: > > > for my first question u say we can put our own input documents in > directory > > that documents also should be of format similar to bayes-train-input. > > If yes, then I generated my input data using PrepareTwentyNewsgroups. > > And used that as my input for testclassifier > > But didn't get expected results. > > As I observed it didn't read my files I my input directory > > I tried replacing one of the files of input directory with one of the > files > > of train-input directory > > Still same result. > > Why is it not reading my files? > > > > Results below : > > > > 10/11/19 10:45:12 INFO datastore.InMemoryBayesDatastore: > > comp.sys.mac.hardware -121323.6282757108 547567.2698760114 > > -0.2215684445551005 > > 2 > > 10/11/19 10:45:12 INFO datastore.InMemoryBayesDatastore: sci.space > > -189203.04544769705 547567.2698760114 -0.3455338838834164 > > 10/11/19 10:45:12 INFO datastore.InMemoryBayesDatastore: rec.motorcycles > > -138625.2628242977 547567.2698760114 -0.25316572127418674 > > 10/11/19 10:45:12 INFO datastore.InMemoryBayesDatastore: rec.autos > > -136935.18434679657 547567.2698760114 -0.25007919917821886 > > 10/11/19 10:45:12 INFO datastore.InMemoryBayesDatastore: comp.graphics > > -161979.38306986375 547567.2698760114 -0.29581640828631267 > > 10/11/19 10:45:12 INFO datastore.InMemoryBayesDatastore: > talk.politics.misc > > -159579.70032298338 547567.2698760114 -0.29143396455949216 > > 10/11/19 10:45:12 INFO datastore.InMemoryBayesDatastore: sci.med > > -183835.5334355675 547567.2698760114 -0.3357314133790253 > > 10/11/19 10:45:12 INFO bayes.TestClassifier: > > ======================================================= > > Summary > > ------------------------------------------------------- > > Correctly Classified Instances : 0 ?% > > Incorrectly Classified Instances : 0 ?% > > Total Classified Instances : 0 > > > > ======================================================= > > Confusion Matrix > > ------------------------------------------------------- > > a b c d e f g h i j > > k l m n o p q r > > s t <--Classified as > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 a = rec.sport.baseball > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 b = sci.crypt > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 c = rec.sport.hockey > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 d = talk.politics.guns > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 e = soc.religion.christian > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 f = sci.electronics > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 g = comp.os.ms-windows.misc > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 h = misc.forsale > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 i = talk.religion.misc > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 j = alt.atheism > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 k = comp.windows.x > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 l = talk.politics.mideast > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 m = comp.sys.ibm.pc.hardware > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 n = comp.sys.mac.hardware > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 o = sci.space > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 p = rec.motorcycles > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 q = rec.autos > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 r = comp.graphics > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 s = talk.politics.misc > > 0 0 0 0 0 0 0 0 0 0 > > 0 0 0 0 0 0 0 0 > > 0 0 | 0 t = sci.med > > Default Category: unknown: 20 > > > > > > 10/11/19 10:45:12 INFO driver.MahoutDriver: Program took 5485 ms > > > > Am I missing anything . > > > > > > Come to my second question, that means we are testing the classifier > > against > > our inputs itself. > > Still I didn't understand. > > What I understood about classification is we have set of documents which > > will act as model for classification of new documents in the system. > > Am I right? > > Doesn't Mahout works in same way ? > > > > Third question, yeah I am looking for Mahout's API for classification. > > > > > > @ Jaganadh - Thanks for clearing my doubts > > > > Regards, > > Divya > > > > > > -----Original Message----- > > From: JAGANADH G [mailto:[email protected]] > > Sent: Friday, November 19, 2010 3:09 PM > > To: [email protected] > > Subject: Re: classification example doubts > > > > > > > > 1) I want to know what should go in "bayes-test-input". > > > > > > > > After preparing the 20news-group data for training you can separate some > > documents for testing your classifier. > > These documents should go to "bayes-test-input". > > > > Or ven you can put a new set of documets in the directory . > > > > > > > 2) If we take Wikipedia example > > > https://cwiki.apache.org/MAHOUT/wikipedia-bayes-example.html > > > > > > > > > > > > To trainclassifier We have used Wikipediainput to generate model . > > > > > > To test classifier again we used wikipediamodel as input and Wikipedia > > > input > > > as test documents directory. > > > > > > I didn't understand why are we doing so ? > > > > > > > > > > We are testing the classifier against the development set we used. > > > > > > > > > 3) Last thing I want to know that when we use run testclassifier > > using > > > command line we can see the output. > > > > > > How can we make use of this output? > > > > > > > > > Are you looking for Mahout API usgae for classification ? > > > > -- > > ********************************** > > JAGANADH G > > http://jaganadhg.freeflux.net/blog > > > > > >
