Hello again
I am trying to run an OneClassSVM() test:
/import/ sklearn.svm.sparse as sp_svm
ocsvm = sp_svm.OneClassSVM(nu=0.5, kernel='linear')
ocsvm.fit( ssp.csr_matrix(train_X, shape=train_X.shape, dtype=np.float64) )
and I am getting the following message:
File
"/home/dimitrios/Development_Workspace/webgenreidentification/src/experiments_lowbow.py",
line 147, in evaluate
ocsvm.fit( ssp.csr_matrix(train_X, shape=train_X.shape,
dtype=np.float64) ) #, train_Y)
File
"/usr/local/lib/python2.6/dist-packages/sklearn/svm/sparse/classes.py",
line 175, in fit
X, [], sample_weight=sample_weight)
File
"/usr/local/lib/python2.6/dist-packages/sklearn/svm/sparse/base.py",
line 22, in fit
return super(SparseBaseLibSVM, self).fit(X, y, sample_weight)
File "/usr/local/lib/python2.6/dist-packages/sklearn/svm/base.py",
line 150, in fit
fit(X, y, sample_weight)
File "/usr/local/lib/python2.6/dist-packages/sklearn/svm/base.py",
line 263, in _sparse_fit
% (X.shape, y.shape))
ValueError: X and y have incompatible shapes: (180, 255) vs (0,)
Note: Sparse matrices cannot be indexed w/boolean masks (use
`indices=True` in CV).
I have used this OneClassSVM() in a previous work from sklearn and it
was working fine.
I cannot tell from the Documentation the reason I am getting such a
message. And I cannot tell what CV is for using `indices=True`
Regards,
Dimitrios
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