Thanks. But if I don't use my own data set and master it properly, I feel
bit shy down. Let me see how it goes. Regards, Subhabrata.


On Sat, Mar 30, 2013 at 4:21 AM, Rolando Espinoza La Fuente <
[email protected]> wrote:

> Hi, What kind of data do you have? Is it text?
>
> Basically, you need to extract/build a feature matrix for your dataset,
> and in the case of supervised learning, the target vector too.
>
> You can take a look at the documentation which includes some functionality
> to build the feature matrix for your data.
>
> http://scikit-learn.org/dev/modules/feature_extraction.html
>
> Building a dataset and selecting the right features can be really hard,
> and for
> what I've read, is where you will spend most of the time. When I tried to
> build a
> training dataset for news classification it turned very biased because it
> had more samples of a particular topic than any other.
>
> Many, if not all, examples of machine learning use an already made dataset
> with good properties and features. Plugging your own data and expecting
> good results it might not be as trivial as you might think.
>
> Regards,
>
> Rolando
>
>
> On Fri, Mar 29, 2013 at 4:17 PM, Subhabrata Banerjee <
> [email protected]> wrote:
>
>> Dear Group,
>>
>> I am a new entrant in the scikit-learn environment. I was trying to check
>> your Naive Bayes Example in
>> http://scikit-learn.org/dev/modules/naive_bayes.html. Here how may we
>> use our own data?
>>
>> If anyone of the estemeed members can kindly suggest.
>>
>> Regards,
>> Subhabrata.
>>
>>
>>
>>
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-- 
*Sree Subhabrata Banerjee*
*PDF(2007-2010)[IISc, Bangalore]*
Call:09873237945
Member, IEEE(USA), ACM(USA).
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Rise to greatness in Intel's independent game demo contest. Compete 
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$5K grand prize plus 10 genre and skill prizes. Submit your demo 
by 6/6/13. http://altfarm.mediaplex.com/ad/ck/12124-176961-30367-2
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