X.shape
(150, 2)
X.dtype
dtype('float64')
Here is how I get the data
from sklearn import datasets
from sklearn.neighbors import KNeighborsClassifier
iris = datasets.load_iris()
X = iris.data[:, :2]
y = iris.target
clf = KNeighborsClassifier(n_neighbors=5, metric="mahalanobis")
clf.fit(X,y)
On 10 July 2014 14:01, Kyle Kastner <[email protected]> wrote:
> OK - what is the result of X.shape and X.dtype? What is X?
>
>
> On Thu, Jul 10, 2014 at 1:55 PM, Sheila the angel <[email protected]>
> wrote:
>
>> Yes, the error is in fit(X,y)
>>
>> clf.fit(X,y)
>>
>>
>> ---------------------------------------------------------------------------
>> Traceback (most recent call last):
>>
>> File "<ipython-input-77-12b5b6bd5106>", line 1, in <module>
>> clf.fit(X,y)
>>
>> File
>> "/usr/local/lib/python2.7/dist-packages/sklearn/neighbors/base.py", line
>> 630, in fit
>> return self._fit(X)
>>
>> File
>> "/usr/local/lib/python2.7/dist-packages/sklearn/neighbors/base.py", line
>> 216, in _fit
>> **self.effective_metric_kwds_)
>>
>> File "binary_tree.pxi", line 1062, in
>> sklearn.neighbors.ball_tree.BinaryTree.__init__
>> (sklearn/neighbors/ball_tree.c:8037)
>>
>> File "dist_metrics.pyx", line 280, in
>> sklearn.neighbors.dist_metrics.DistanceMetric.get_metric
>> (sklearn/neighbors/dist_metrics.c:4066)
>>
>> File "dist_metrics.pyx", line 636, in
>> sklearn.neighbors.dist_metrics.MahalanobisDistance.__init__
>> (sklearn/neighbors/dist_metrics.c:7162)
>>
>> File "/usr/lib/python2.7/dist-packages/numpy/linalg/linalg.py", line
>> 510, in inv
>> _assertRankAtLeast2(a)
>>
>> File "/usr/lib/python2.7/dist-packages/numpy/linalg/linalg.py", line
>> 202, in _assertRankAtLeast2
>> 'at least two-dimensional' % len(a.shape))
>>
>> LinAlgError: 0-dimensional array given. Array must be at least
>> two-dimensional
>>
>>
>>
>>
>> On 10 July 2014 13:36, Danny Sullivan <[email protected]> wrote:
>>
>>> Hi Sheila,
>>>
>>> That looks right, I'm guessing you're getting an error when performing
>>> the fit, not when setting the metric. What's the error you're getting?
>>>
>>>
>>> On 7/10/14, 11:45 AM, Sheila the angel wrote:
>>>
>>> What is the correct way to use different metric in KNeighborsClassifier
>>> ?
>>>
>>> I tried this
>>>
>>> clf = KNeighborsClassifier(metric="mahalanobis").fit(X, y)
>>>
>>> which give me error.
>>>
>>>
>>> Thanks
>>> --
>>> Sheila
>>>
>>>
>>> ------------------------------------------------------------------------------
>>> Open source business process management suite built on Java and Eclipse
>>> Turn processes into business applications with Bonita BPM Community Edition
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>>>
>>>
>>> _______________________________________________
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>>> [email protected]https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
>>>
>>>
>>>
>>>
>>> ------------------------------------------------------------------------------
>>> Open source business process management suite built on Java and Eclipse
>>> Turn processes into business applications with Bonita BPM Community
>>> Edition
>>> Quickly connect people, data, and systems into organized workflows
>>> Winner of BOSSIE, CODIE, OW2 and Gartner awards
>>> http://p.sf.net/sfu/Bonitasoft
>>> _______________________________________________
>>> Scikit-learn-general mailing list
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>>>
>>>
>>
>>
>> ------------------------------------------------------------------------------
>> Open source business process management suite built on Java and Eclipse
>> Turn processes into business applications with Bonita BPM Community
>> Edition
>> Quickly connect people, data, and systems into organized workflows
>> Winner of BOSSIE, CODIE, OW2 and Gartner awards
>> http://p.sf.net/sfu/Bonitasoft
>> _______________________________________________
>> Scikit-learn-general mailing list
>> [email protected]
>> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
>>
>>
>
>
> ------------------------------------------------------------------------------
> Open source business process management suite built on Java and Eclipse
> Turn processes into business applications with Bonita BPM Community Edition
> Quickly connect people, data, and systems into organized workflows
> Winner of BOSSIE, CODIE, OW2 and Gartner awards
> http://p.sf.net/sfu/Bonitasoft
> _______________________________________________
> Scikit-learn-general mailing list
> [email protected]
> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
>
>
------------------------------------------------------------------------------
Open source business process management suite built on Java and Eclipse
Turn processes into business applications with Bonita BPM Community Edition
Quickly connect people, data, and systems into organized workflows
Winner of BOSSIE, CODIE, OW2 and Gartner awards
http://p.sf.net/sfu/Bonitasoft
_______________________________________________
Scikit-learn-general mailing list
[email protected]
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
