Hi, I am not sure how your custom metric works, but would a np.where(x >= 0.5,
1., 0.) work in your case?
> On Jan 12, 2016, at 1:08 PM, A neuman <themagenta...@gmail.com> wrote:
>
> Sorry, thats not right what I wrote:
> X:
> [ 0.6371319 0.54557285 0.30214217 0.14690307 0.49778446 0.89183238
> 0.52445514 0.63379164 0.71873681 0.55008567]
>
> Y:
> [ 0.6371319 0.54557285 0.30214217 0.14690307 0.49778446 0.89183238
> 0.52445514 0.63379164 0.71873681 0.55008567]
>
> X:
> [ 0. 0. 0. 0.02358491 0.00471698 0. 0.
> 0. 0. 0.00471698 0.00471698 0.00471698 0.02830189
> 0.00943396 0. .............................52358491 0.53773585
> 0.63207547 0.51886792 0.66037736 0.75 0.57075472 0.59433962
> 0.63679245 0.8490566 0.71698113 0.02358491]
>
> Y:
> [ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
> 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
> 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
> 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0.
> 1. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
> 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
> 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
> 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0.
> 0. 0. 0. 0. 0. 1. 0. 0. 1. 0. 1. 0. 0. 1. 0. 1. 1. 0.
> 1. 1. 1. 1. 0.]
>
> and so on..
>
> but X should be also containing 1's and 0's.
>
> best,
>
> On 12 January 2016 at 19:04, A neuman <themagenta...@gmail.com
> <mailto:themagenta...@gmail.com>> wrote:
> Hey,
>
> I Have an another problem,
>
> if I'm using my own metric, there are not only the samples in x and y.
> I'm using a 10 fold cv with k-NN Classifier.
> My Attributes are only 1's and 0's, but if im printing them out, I'll get:
>
> KNeighborsClassifier(metric=myFunc)
>
> def myFunc(x,y):
>
> print x,'\n'
> print y,'\n'
>
> I Cutted some values due to the size:
>
> Thats for x:
>
> [ 0.6371319 0.54557285 0.30214217 0.14690307 0.49778446 0.89183238
> 0.52445514 0.63379164 0.71873681 0.55008567]
>
> [ 0.6371319 0.54557285 0.30214217 0.14690307 0.49778446 0.89183238
> 0.52445514 0.63379164 0.71873681 0.55008567]
>
> [ 0. 0. 0. 0.02358491 0.00471698 0. 0.
> 0. 0. 0.00471698 0.00471698 0.00471698 0.02830189
> 0.00943396 0. .............................52358491 0.53773585
> 0.63207547 0.51886792 0.66037736 0.75 0.57075472 0.59433962
> 0.63679245 0.8490566 0.71698113 0.02358491]
>
> [ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
> 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
> 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
> 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0.
> 1. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
> 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
> 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
> 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0.
> 0. 0. 0. 0. 0. 1. 0. 0. 1. 0. 1. 0. 0. 1. 0. 1. 1. 0.
> 1. 1. 1. 1. 0.]
>
>
>
> and for y
>
> [ 0. 0. 0. 0.02358491 0.00471698 0. 0.
> 0. 0. 0.00471698 0.00471698 0.00471698 0.02830189
> 0. ..........
> 0.63207547 0.51886792 0.66037736 0.75 0.57075472 0.59433962
> 0.63679245 0.8490566 0.71698113 0.02358491]
>
> [ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
> 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 1. 0. 0.
> 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
> 0. 1. 0. 0. 1. 0. 1. 1. 0. 0. 0. 0. 0. 1. 0. 0. 1. 0.
> 0. 1. 1. 0. 0. 1. 0. 0. 0. 1. 0. 0. 0. 0. 1. 0. 1. 0.
> 0. 0. 0. 1. 1. 0. 0. 0. 0. 0. 0. 0. 1. 1. 0. 0. 1. 1.
> 0. 0. 0. 0. 1. 0. 0. 0. 0. 1. 0. 0. 0. 0. 1. 0. 1. 0.
> 0. 0. 0. 0. 1. 0. 0. 1. 1. 1. 1. 0. 0. 0. 0. 0. 1. 0.
> 0. 0. 0. 0. 1. 1. 0. 0. 0. 0. 0. 0. 1. 0. 1. 1. 1. 1.
> 1. 1. 1. 1. 0.]
>
>
> The problem is, I have to count the occurences from 0's and 1's in x and y.
> And if there are some other arrays
> lik 0.636..... I dont get the right solution. So in general, i only want the
> array with 1 and 0
>
> best,
>
>
>
>
>
>
>
>
>
>
>
>
>
> On 9 January 2016 at 03:58, A neuman <themagenta...@gmail.com
> <mailto:themagenta...@gmail.com>> wrote:
> Ah, that helped me a lot!!!
>
> So i just write my own function that returns an skalar. This function is used
> in the metric parameter of the kNN function.
>
> Thank you!!!
>
>
> On 9 January 2016 at 03:41, Sebastian Raschka <se.rasc...@gmail.com
> <mailto:se.rasc...@gmail.com>> wrote:
> You could just need “regular" Python function that outputs a scalar. For
> example, consider the following example:
>
> >>> from sklearn.neighbors import NearestNeighbors
> >>> import numpy as np
> >>> X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
> >>> nbrs = NearestNeighbors(n_neighbors=2, algorithm='ball_tree').fit(X)
> >>> distances, indices = nbrs.kneighbors(X)
> >>> distances
> array([[ 0. , 1. ],
> [ 0. , 1. ],
> [ 0. , 1.41421356],
> [ 0. , 1. ],
> [ 0. , 1. ],
> [ 0. , 1.41421356]])
>
> (note that I am using the NearestNeighbors class here, but the same applies
> to the KNeighborsClassifier)
>
> For example, to compute the distances between samples as Euclidean distance
> (the default) you could just define a Python function
>
> >>> def eucldist(x, y):
> ... return np.sqrt(np.sum((x-y)**2))
> >>> nbrs = NearestNeighbors(n_neighbors=2, algorithm='ball_tree',
> >>> metric=eucldist).fit(X)
> >>> distances, indices = nbrs.kneighbors(X)
> >>> distances
> array([[ 0. , 1. ],
> [ 0. , 1. ],
> [ 0. , 1.41421356],
> [ 0. , 1. ],
> [ 0. , 1. ],
> [ 0. , 1.41421356]])
>
> (alt. you could provide it as lambda function)
>
> Best,
> Sebastian
>
> > On Jan 8, 2016, at 9:19 PM, A neuman <themagenta...@gmail.com
> > <mailto:themagenta...@gmail.com>> wrote:
> >
> > Hello everyone,
> >
> > I actually want to use the KNeighboursClassifier, with my own distances.
> >
> > in the Documentation stands the following:
> >
> > [callable] : a user-defined function which accepts an array of distances,
> > and returns an array of the same shape containing the weights.
> >
> > I just dont know, how should the array looks like?
> >
> > For example, if I have 100 Samples, the array has a size 100*100?
> > So for every samples there is a distance to the other 99 samples.
> >
> > [[0.4, 0.2, ...],[0.3,0.1,...]........[0.9,0.6,...]] something like this?
> >
> > I would appreciate your help.
> >
> > best,
> >
> >
> > ------------------------------------------------------------------------------
> > Site24x7 APM Insight: Get Deep Visibility into Application Performance
> > APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month
> > Monitor end-to-end web transactions and take corrective actions now
> > Troubleshoot faster and improve end-user experience. Signup Now!
> > http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140_______________________________________________
> >
> > <http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140_______________________________________________>
> > Scikit-learn-general mailing list
> > Scikit-learn-general@lists.sourceforge.net
> > <mailto:Scikit-learn-general@lists.sourceforge.net>
> > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
> > <https://lists.sourceforge.net/lists/listinfo/scikit-learn-general>
>
>
> ------------------------------------------------------------------------------
> Site24x7 APM Insight: Get Deep Visibility into Application Performance
> APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month
> Monitor end-to-end web transactions and take corrective actions now
> Troubleshoot faster and improve end-user experience. Signup Now!
> http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140
> <http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140>
> _______________________________________________
> Scikit-learn-general mailing list
> Scikit-learn-general@lists.sourceforge.net
> <mailto:Scikit-learn-general@lists.sourceforge.net>
> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
> <https://lists.sourceforge.net/lists/listinfo/scikit-learn-general>
>
>
>
> ------------------------------------------------------------------------------
> Site24x7 APM Insight: Get Deep Visibility into Application Performance
> APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month
> Monitor end-to-end web transactions and take corrective actions now
> Troubleshoot faster and improve end-user experience. Signup Now!
> http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140_______________________________________________
> Scikit-learn-general mailing list
> Scikit-learn-general@lists.sourceforge.net
> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
------------------------------------------------------------------------------
Site24x7 APM Insight: Get Deep Visibility into Application Performance
APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month
Monitor end-to-end web transactions and take corrective actions now
Troubleshoot faster and improve end-user experience. Signup Now!
http://pubads.g.doubleclick.net/gampad/clk?id=267308311&iu=/4140
_______________________________________________
Scikit-learn-general mailing list
Scikit-learn-general@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
