the target
values, which is disastrous if y is continuous.
Is there a way to train logistic regression on a continuous target variable
in sklearn?
Any help is highly appreciated.
Best,
George.
--
George Bezerra
tic regression is a classifier, not a
> regressor — the name is misleading, I agree. I think you may want to look
> into regression analysis for your continuous target variable.
>
> Best,
> Sebastian
>
> > On Oct 3, 2015, at 9:58 PM, George Bezerra wrote:
> >
> >
*I meant section 5.
On Sat, Oct 3, 2015 at 11:07 PM, George Bezerra wrote:
> Thanks Sebastian.
>
> I am trying to follow this paper:
> http://research.microsoft.com/en-us/um/people/mattri/papers/www2007/predictingclicks.pdf
> (check out section 6.2). They use logistic regression
probabilities
>> sum up to 1). In any case, logistic regression works with nominal class
>> labels - categorical class labels with no order implied.
>>
>> To keep a long story short: Logistic regression is a classifier, not a
>> regressor — the name is misleading, I agree
the source code for this algorithm so that I can
take a look?
Thanks,
George.
--
George Bezerra
--
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.
Any ideas/experience with this?
Thanks!
--
George Bezerra
--
HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions
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gt; would query the model with some input data and the model would spit out the
>> result.
>>
>> Any ideas/experience with this?
>>
>> Thanks!
>>
>> --
>> George Bezerra
>>
>>
>>
find the source code for this algorithm so that I can
take a look?
Thanks,
George.
--
George Bezerra
--
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-general mailing list
> Scikit-learn-general@lists.sourceforge.net
> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
>
>
--
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I'm using the LinearSVC module but I noticed that it doesn't implement a
predict_proba method, only the decision_function method.
Is there a simple way to get the probabilities that a data point belongs to
a class for this model?
Thanks.
--
Geor
On Thu, Oct 23, 2014 at 10:34 AM, Lars Buitinck wrote:
> 2014-10-23 16:21 GMT+02:00 George Bezerra :
> > Is there a simple way to get the probabilities that a data point belongs
> to
> > a class for this model?
>
> SVMs aren't probability models. You can use Logisti
al=True
Is there a way to avoid this problem?
Thanks,
George.
--
George Bezerra
--
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nalty':'l2', 'loss': 'l2', 'C': : 10. **
>> np.arange(-3, 3)}]
>>
>> or something like that. (Look up the allowed combination in the docs, I
>> don't know them by heart ;)
>>
>> What are you searching over? Searching ove
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