You really need to provide more details with what exactly you're stuck with. If you've extracted useful features from some image into a matrix X with binary labels y you can just do `clf.fit(X, y)` to train the classifier.
On Sat, Mar 18, 2017 at 10:21 PM, Afzal Ansari <b113...@iiit-bh.ac.in> wrote: > Hello Sir, > I want to classify images containing negative and positive samples using > Adaboost classifier. So how can I do that classification? Please help me > regarding this. > > Thanks. > > On Sat, Mar 18, 2017 at 11:03 PM, Francois Dion <francois.d...@gmail.com> > wrote: > >> You need to provide more details on exactly what you need. I'll take a >> stab at it: >> >> Are you trying to replicate OpenCV cascade training? >> If so, what they call DAB is Scikit learn adaboostclassifier ( >> http://scikit-learn.org/stable/modules/generated/sklearn. >> ensemble.AdaBoostClassifier.html) with algorithm=SAMME. >> RAB is SAMME.R. >> >> >> Francois >> >> >> Sent from my BlackBerry 10 Darkphone >> *From: *Afzal Ansari >> *Sent: *Saturday, March 18, 2017 00:51 >> *To: *scikit-learn@python.org >> *Reply To: *Scikit-learn user and developer mailing list >> *Subject: *[scikit-learn] Regarding Adaboost classifier >> >> Hello Developers! >> I am currently working on feature extraction method which is based on >> Haar features for image classification. I am unable to find pure >> implementation of adaboost classifier algorithm on the internet even on >> scikit learn web. I need to train the classifier using adaboost classifier >> to obtain Haar features from image dataset. >> Please help me regarding this code. Reply soon. >> >> Thanks in advance. >> >> >> _______________________________________________ >> scikit-learn mailing list >> scikit-learn@python.org >> https://mail.python.org/mailman/listinfo/scikit-learn >> >> > > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > >
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