hum... If it does not work either with LogisticRegression than something definitely got broken unless the fix was only affecting the predict_proba
Alex On Mon, Mar 26, 2012 at 3:02 PM, Andreas <[email protected]> wrote: > Hi. > Which version of scikit-learn are you using? > Andy > > > > On 03/26/2012 03:07 PM, xinfan meng wrote: > > Alex, I am afraid some codes have been broken... > > In [127]: X = [[0], [1]] > > In [129]: Y = [0, 1] > > In [130]: clf.fit(X, Y) > Out[130]: > SVC(C=1.0, cache_size=200, coef0=0.0, degree=3, gamma=0.0, kernel='linear', > probability=False, scale_C=False, shrinking=True, tol=0.001) > > In [132]: clf.decision_function(X) > Out[132]: > array([[-0.5], > [ 0.5]]) > > In [133]: X2 = [[1], [0]] > > In [134]: Y2 = [1, 0] > > In [135]: clf.fit(X2, Y2) > Out[135]: > SVC(C=1.0, cache_size=200, coef0=0.0, degree=3, gamma=0.0, kernel='linear', > probability=False, scale_C=False, shrinking=True, tol=0.001) > > In [137]: clf.decision_function(X2) > Out[137]: > array([[ 0.5], > [-0.5]]) > > On Mon, Mar 26, 2012 at 8:59 PM, Alexandre Gramfort > <[email protected]> wrote: >> >> hi, >> >> from what I remember we fixed the random label ordering problem >> at least for the 2 classes case. >> >> can you check that things behave fine and the same way with Y = [0, >> 1] and Y = [1, 0]? >> >> Alex >> >> On Mon, Mar 26, 2012 at 5:00 AM, xinfan meng <[email protected]> wrote: >> > I use the following codes to obtain decision values for SVC classifier >> > clf. >> > >> > >> > ----------------------------------------------------------------------------------------------- >> > >> > In [5]: >>> clf = svm.SVC() >> > >> > In [23]: >>> X = [[0], [1], [2]] >> > >> > In [24]: >>> Y = [0, 1, 2] >> > >> > In [25]: clf.fit(X, Y) >> > Out[25]: >> > SVC(C=1.0, cache_size=200, coef0=0.0, degree=3, gamma=1.0, kernel='rbf', >> > probability=False, scale_C=False, shrinking=True, tol=0.001) >> > >> > In [26]: clf.predict([[0]]) >> > Out[26]: array([ 0.]) >> > >> > In [27]: clf.predict(X) >> > Out[27]: array([ 0., 1., 2.]) >> > >> > In [28]: clf.decision_function(X) >> > Out[28]: >> > array([[-0.63212056, -0.98168436, -0.3495638 ], >> > [ 0.63212056, -0. , -0.63212056], >> > [ 0.3495638 , 0.98168436, 0.63212056]]) >> > >> > >> > ----------------------------------------------------------------------------------------------- >> > >> > >> > >> > The decision_function return confusing results. Why [-0.63212056, >> > -0.98168436, -0.3495638 ] corresponds to label 0 ? >> > The encoding of labels seems to be different from the natural orders of >> > (0, >> > 1, 2 ...) . >> > After reading the README file of LibSVM, I found the label encoding can >> > be >> > obtained by calling svm_get_labels(). >> > Where can I find this function wrapper in sklearn? Without that, the >> > return >> > results of decision_function() are difficult to interpret. >> > Thanks! >> > >> > -- >> > Best Wishes >> > -------------------------------------------- >> > Meng Xinfan（蒙新泛） >> > Institute of Computational Linguistics >> > Department of Computer Science & Technology >> > School of Electronic Engineering & Computer Science >> > Peking University >> > Beijing, 100871 >> > China >> > >> > >> > ------------------------------------------------------------------------------ >> > This SF email is sponsosred by: >> > Try Windows Azure free for 90 days Click Here >> > http://p.sf.net/sfu/sfd2d-msazure >> > _______________________________________________ >> > Scikit-learn-general mailing list >> > [email protected] >> > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general >> > >> >> >> ------------------------------------------------------------------------------ >> This SF email is sponsosred by: >> Try Windows Azure free for 90 days Click Here >> http://p.sf.net/sfu/sfd2d-msazure >> _______________________________________________ >> Scikit-learn-general mailing list >> [email protected] >> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > > > > > -- > Best Wishes > -------------------------------------------- > Meng Xinfan（蒙新泛） > Institute of Computational Linguistics > Department of Computer Science & Technology > School of Electronic Engineering & Computer Science > Peking University > Beijing, 100871 > China > > ------------------------------------------------------------------------------ > This SF email is sponsosred by: > Try Windows Azure free for 90 days Click Here > http://p.sf.net/sfu/sfd2d-msazure > > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > > > > > ------------------------------------------------------------------------------ > This SF email is sponsosred by: > Try Windows Azure free for 90 days Click Here > http://p.sf.net/sfu/sfd2d-msazure > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > ------------------------------------------------------------------------------ This SF email is sponsosred by: Try Windows Azure free for 90 days Click Here http://p.sf.net/sfu/sfd2d-msazure _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
