When using gradient boosting, my understanding is that samples that were
misclassified are more emphasized.
Which particular algorithm is used for classification?
Thank you,
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Emanuele,
I just realized that the above approach might not be what you actually
want: It will select the best value for ``n_estimators`` for _each_
fold - what we actually should do is to average the staged scores over
all folds and select the ``n_estimators`` which has the best average
score.
I
On 06/21/2012 06:08 PM, Andreas Mueller wrote:
> Hi Emanuele, hi Peter.
> @Emanuele: You could also try to use IterGrid instead of GridSearchCV.
> This might mean having to do some things by hand, but should work.
>
> @Peter: Could your improvements also be applied to RandomForests
> an the oob sco
On 06/21/2012 06:04 PM, Peter Prettenhofer wrote:
> 2012/6/21 Emanuele Olivetti:
>> Dear All,
>>
>> I am interested in attempting model selection with GridSearchCV() on
>> GradientBoostingRegressor(). I am quite new to boosting but I see from
>> the nice examples in sklearn documentation [0] that o
2012/6/21 Andreas Mueller :
> Hi Emanuele, hi Peter.
> @Emanuele: You could also try to use IterGrid instead of GridSearchCV.
> This might mean having to do some things by hand, but should work.
>
> @Peter: Could your improvements also be applied to RandomForests
> an the oob score? Having a method
Hi Emanuele, hi Peter.
@Emanuele: You could also try to use IterGrid instead of GridSearchCV.
This might mean having to do some things by hand, but should work.
@Peter: Could your improvements also be applied to RandomForests
an the oob score? Having a method there would also be quite nice.
Cheer
2012/6/21 Emanuele Olivetti :
> Dear All,
>
> I am interested in attempting model selection with GridSearchCV() on
> GradientBoostingRegressor(). I am quite new to boosting but I see from
> the nice examples in sklearn documentation [0] that once the n_estimator
> is fixed, it is possible to evalua
Dear All,
I am interested in attempting model selection with GridSearchCV() on
GradientBoostingRegressor(). I am quite new to boosting but I see from
the nice examples in sklearn documentation [0] that once the n_estimator
is fixed, it is possible to evaluate the classifiers at each boosting
itera
