Thank you Peter, your answer if very helpful!

Best,
--Issam

On 03/08/2013 01:40 PM, Peter Prettenhofer wrote:
> Issam,
>
> currently, GaussianNB does not support sample weights thus it cannot
> be used w/ Adaboost.
> In Weka, if a classifier does not support sample weights they fall
> back to data set re-sampling. We could implement this strategy as well
> but it would not be very efficient due to the data structures that we
> use internally (i.e. numpy arrays).
>
> best,
>   Peter
>
> 2013/3/7 Issam <issamo...@gmail.com>:
>> Evening Dear Developers!
>>
>> I'm peculiarly getting an error while using AdaBoostClassifier with
>> GaussianNB() as a a base estimator.
>>
>> These are my commands
>>
>> In [65]: gnb = GaussianNB()
>> In [66]: bdt = AdaBoostClassifier(gnb,n_estimators=100)
>> In [67]: bdt.fit(X,y)
>>
>> I get the following error after executing "In[67]" :
>>
>> TypeError: fit() got an unexpected keyword argument 'sample_weight'
>>
>> Any reason why I might be getting this?
>>
>> PS: I frequently use adaboosting with Navie Bayes as a base classifier in
>> WEKA, hence the concern :)
>>
>> Thank you very much!
>>
>> Best regards,
>> --Issam Laradji
>>
>>
>>
>>
>>
>>
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>
>


------------------------------------------------------------------------------
Symantec Endpoint Protection 12 positioned as A LEADER in The Forrester  
Wave(TM): Endpoint Security, Q1 2013 and "remains a good choice" in the  
endpoint security space. For insight on selecting the right partner to 
tackle endpoint security challenges, access the full report. 
http://p.sf.net/sfu/symantec-dev2dev
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