X = np.array(...,dtype=np.float64).astype(np.float)
y = np.array(...,dtype=np.float64).astype(np.float)
print(X)
[[-0.5 0. ]
[ 0. 0. ]
[ 0. 0. ]
[ 0. 0. ]
[ 0. -3.5]
[-3.5 -3.5]
[-3.5 -2. ]
[-2. 0. ]
[ 0. 0. ]
[ 0. -3. ]]
print(y)
[-3.5 -3.5 -3.5 -3.5 -3.5 -2. -3. -3. -3. 1. ]
(10, 2)
(10,)
from sklearn.naive_bayes import GaussianNB
clf = GaussianNB()
clf.fit(X, Y)
Неважно, что я получу,
Traceback (most recent call last):
File "scripts/wave-pool.py", line 174, in <module>
clf.fit(X, y)
File "/home/ben/.local/lib/python2.7/site-packages/sklearn/naive_bayes.py", line 192, in fit
sample_weight=sample_weight)
File "/home/ben/.local/lib/python2.7/site-packages/sklearn/naive_bayes.py", line 355, in _partial_fit
if _check_partial_fit_first_call(self, classes):
File "/home/ben/.local/lib/python2.7/site-packages/sklearn/utils/multiclass.py", line 320, in _check_partial_fit_first_call
clf.classes_ = unique_labels(classes)
File "/home/ben/.local/lib/python2.7/site-packages/sklearn/utils/multiclass.py", line 96, in unique_labels
raise ValueError("Unknown label type: %s" % repr(ys))
ValueError: Unknown label type: (array([-3.5, -3. , -2. , 1. ]),)