[scikit-learn] Regarding Adaboost classifier

[Afzal Ansari]

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.dion at 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 at 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.
>
>
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