The minimum number of groups for any class cannot be less than 2 error
$begingroup$
cv_split = StratifiedShuffleSplit(n_splits=10, test_size=0.3, random_state=0)
# Performing cross-validation to estimate the performance of the models
for idx, est in enumerate(estimator):
cv_results = cross_validate(est[1](), x_value, y_value, cv=cv_split)
I got following error from this code
ValueError: The least populated class in y has only 1 member, which is
too few. The minimum number of groups for any class cannot be less
than 2.
and my y_value looks like
y_value = array([221900, 180000, 510000, ..., 360000, 400000, 325000])
I used this method before and y_value has the same shape as before.
python data-mining cross-validation
$endgroup$
add a comment |
$begingroup$
cv_split = StratifiedShuffleSplit(n_splits=10, test_size=0.3, random_state=0)
# Performing cross-validation to estimate the performance of the models
for idx, est in enumerate(estimator):
cv_results = cross_validate(est[1](), x_value, y_value, cv=cv_split)
I got following error from this code
ValueError: The least populated class in y has only 1 member, which is
too few. The minimum number of groups for any class cannot be less
than 2.
and my y_value looks like
y_value = array([221900, 180000, 510000, ..., 360000, 400000, 325000])
I used this method before and y_value has the same shape as before.
python data-mining cross-validation
$endgroup$
add a comment |
$begingroup$
cv_split = StratifiedShuffleSplit(n_splits=10, test_size=0.3, random_state=0)
# Performing cross-validation to estimate the performance of the models
for idx, est in enumerate(estimator):
cv_results = cross_validate(est[1](), x_value, y_value, cv=cv_split)
I got following error from this code
ValueError: The least populated class in y has only 1 member, which is
too few. The minimum number of groups for any class cannot be less
than 2.
and my y_value looks like
y_value = array([221900, 180000, 510000, ..., 360000, 400000, 325000])
I used this method before and y_value has the same shape as before.
python data-mining cross-validation
$endgroup$
cv_split = StratifiedShuffleSplit(n_splits=10, test_size=0.3, random_state=0)
# Performing cross-validation to estimate the performance of the models
for idx, est in enumerate(estimator):
cv_results = cross_validate(est[1](), x_value, y_value, cv=cv_split)
I got following error from this code
ValueError: The least populated class in y has only 1 member, which is
too few. The minimum number of groups for any class cannot be less
than 2.
and my y_value looks like
y_value = array([221900, 180000, 510000, ..., 360000, 400000, 325000])
I used this method before and y_value has the same shape as before.
python data-mining cross-validation
python data-mining cross-validation
asked 5 mins ago
monkmonk
113
113
add a comment |
add a comment |
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