Hi,
While using Gaussian Process, I get the following errors and I'm unable to
figure out why.
---------------------------------------------------------------------------ValueError
Traceback (most recent call
last)<ipython-input-93-417d3b33b0b2> in <module>()----> 1 xtrain,
xtest, ytrain, ytest = cross_validation.train_test_split(training,
labels) 2 3 gp = GaussianProcess() 4
gp.fit(xtrain,ytrain) 5
/usr/local/Cellar/python/2.7.6/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/sklearn/cross_validation.pyc
in train_test_split(*arrays, **options) 1510 test_size =
0.25 1511 -> 1512 arrays = check_arrays(*arrays, **options)
1513 n_samples = arrays[0].shape[0] 1514 cv =
ShuffleSplit(n_samples, test_size=test_size,
/usr/local/Cellar/python/2.7.6/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/sklearn/utils/validation.pyc
in check_arrays(*arrays, **options) 261 else:
262 array = np.asarray(array, dtype=dtype)--> 263
_assert_all_finite(array) 264 265 if
array.ndim >= 3:
/usr/local/Cellar/python/2.7.6/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/sklearn/utils/validation.pyc
in _assert_all_finite(X) 40 and not
np.isfinite(X).all()): 41 raise ValueError("Input contains
NaN, infinity"---> 42 " or a value too large
for %r." % X.dtype) 43 44
ValueError: Input contains NaN, infinity or a value too large for
dtype('float64').
The array does not contain any NaNs and Ive also tried scaling the array
but the same error is thrown.
Any help would be appreciated.
Thank you,
--
Regards
Abhishek Thakur
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