[scikit-learn] NuSVC and ValueError: specified nu is infeasible
Thomas Evangelidis
tevang3 at gmail.com
Wed Dec 7 18:07:35 EST 2016
Greetings,
I want to use the Nu-Support Vector Classifier with the following input
data:
X= [
array([ 3.90387012, 1.60732281, -0.33315799, 4.02770896,
1.82337731, -0.74007214, 6.75989219, 3.68538903,
..................
0. , 11.64276776, 0. , 0. ]),
array([ 3.36856769e+00, 1.48705816e+00, 4.28566992e-01,
3.35622071e+00, 1.64046508e+00, 5.66879661e-01,
.....................
4.25335335e+00, 1.96508829e+00, 8.63453394e-06]),
array([ 3.74986249e+00, 1.69060713e+00, -5.09921270e-01,
3.76320781e+00, 1.67664455e+00, -6.21126735e-01,
..........................
4.16700259e+00, 1.88688784e+00, 7.34729942e-06]),
.......
]
and
Y= [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
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, 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]
> Each array of X contains 60 numbers and the dataset consists of 48
> positive and 1230 negative observations. When I train an svm.SVC()
> classifier I get quite good predictions, but wit the svm.NuSVC() I keep
> getting the following error no matter which value of nu in [0.1, ..., 0.9,
> 0.99, 0.999, 0.9999] I try:
> /usr/local/lib/python2.7/dist-packages/sklearn/svm/base.pyc in fit(self,
> X, y, sample_weight)
> 187
> 188 seed = rnd.randint(np.iinfo('i').max)
> --> 189 fit(X, y, sample_weight, solver_type, kernel,
> random_seed=seed)
> 190 # see comment on the other call to np.iinfo in this file
> 191
> /usr/local/lib/python2.7/dist-packages/sklearn/svm/base.pyc in
> _dense_fit(self, X, y, sample_weight, solver_type, kernel, random_seed)
> 254 cache_size=self.cache_size, coef0=self.coef0,
> 255 gamma=self._gamma, epsilon=self.epsilon,
> --> 256 max_iter=self.max_iter, random_seed=random_seed)
> 257
> 258 self._warn_from_fit_status()
> /usr/local/lib/python2.7/dist-packages/sklearn/svm/libsvm.so in
> sklearn.svm.libsvm.fit (sklearn/svm/libsvm.c:2501)()
> ValueError: specified nu is infeasible
Does anyone know what might be wrong? Could it be the input data?
thanks in advance for any advice
Thomas
--
======================================================================
Thomas Evangelidis
Research Specialist
CEITEC - Central European Institute of Technology
Masaryk University
Kamenice 5/A35/1S081,
62500 Brno, Czech Republic
email: tevang at pharm.uoa.gr
tevang3 at gmail.com
website: https://sites.google.com/site/thomasevangelidishomepage/
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