Setting a default value for base_estimator solves the problem.
Thank you.
Maheshakya
On Tue, Sep 17, 2013 at 4:59 PM, Lars Buitinck wrote:
> 2013/9/17 Maheshakya Wijewardena :
> > def __init__(self, base_estimator, n_estimators=10, max_samples=1.0,
>
> You need a default value for base_estimat
2013/9/17 Maheshakya Wijewardena :
> def __init__(self, base_estimator, n_estimators=10, max_samples=1.0,
You need a default value for base_estimator.
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2013/9/17 Maheshakya Wijewardena :
> this is the __init__ function.
>
>
> def __init__(self, base_estimator, n_estimators=10, max_samples=1.0,
> bootstrap=True, oob_score=False, n_jobs=1,
> random_state=None, verbose=0):
> if base_estimator == None:
> base_estimator = DecisionTr
This is the __init__ function of the parent class.
(Above class is inherited from this and RegressorMixin)
@abstractmethod
def __init__(self, base_estimator=None, n_estimators=10,
max_samples=1.0,
bootstrap=True, oob_score=False, n_jobs=1,
random_st
this is the __init__ function.
def __init__(self, base_estimator, n_estimators=10, max_samples=1.0,
bootstrap=True, oob_score=False, n_jobs=1,
random_state=None, verbose=0):
if base_estimator == None:
base_estimator = DecisionTreeRegressor
super(Baggin
On Tue, Sep 17, 2013 at 03:32:26PM +0530, Maheshakya Wijewardena wrote:
> @Lars: I have followed the coding guidelines.
In particular:
http://scikit-learn.org/dev/developers/index.html#rolling-your-own-estimator
?
> It doesn't seems that this problem is related to that.
The test failure that yo
Email the code of the __init__ function of your classifier.
On 17 September 2013 20:02, Maheshakya Wijewardena
wrote:
> @Lars: I have followed the coding guidelines. It doesn't seems that this
> problem is related to that.
>
> @Robert: I didn't get what do you mean by copy paste. Can you elabora
@Lars: I have followed the coding guidelines. It doesn't seems that this
problem is related to that.
@Robert: I didn't get what do you mean by copy paste. Can you elaborate.
On Tue, Sep 17, 2013 at 2:53 PM, Robert Layton wrote:
> Also, are you able to copy paste your __init__ function?
>
>
>
Also, are you able to copy paste your __init__ function?
On 17 September 2013 19:14, Lars Buitinck wrote:
> 2013/9/17 Maheshakya Wijewardena :
> > I have initialized my estimator(those I created) with default classifiers
> > and regressors. But still, I get the same error.
>
> Did you read and
2013/9/17 Maheshakya Wijewardena :
> I have initialized my estimator(those I created) with default classifiers
> and regressors. But still, I get the same error.
Did you read and follow the coding guidelines?
http://scikit-learn.org/stable/developers/index.html#coding-guidelines
-
I have initialized my estimator(those I created) with default classifiers
and regressors. But still, I get the same error.
On Tue, Sep 17, 2013 at 10:26 AM, Robert Layton wrote:
> scikit-learn classifiers should have default values for all __init__
> parameters (except, of course `self`). Set a
scikit-learn classifiers should have default values for all __init__
parameters (except, of course `self`). Set a default for each and the tests
will pass this point.
On 17 September 2013 14:53, Maheshakya Wijewardena
wrote:
> Yes. I have some classes inherited from ClassifierMixin and
> Regress
Yes. I have some classes inherited from ClassifierMixin and RegressorMixin.
So what can be done to resolve this?
On Tue, Sep 17, 2013 at 10:09 AM, Robert Layton wrote:
> If you used the Mixin classes to build a classifier, they will get tested
> here automatically.
> Is that what you did?
>
>
>
If you used the Mixin classes to build a classifier, they will get tested
here automatically.
Is that what you did?
On 17 September 2013 14:35, Maheshakya Wijewardena
wrote:
> I added my own features and tried to run make command. But while the
> process I get the following error trace and the m
I added my own features and tried to run make command. But while the
process I get the following error trace and the making halts.
ERROR: sklearn.tests.test_common.test_all_estimators
--
Traceback (most recent call last):
File
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