Multi-label compute class weight - unhashable type2019 Community Moderator ElectionMulti-label Text ClassificationKMeans clustering to help label Multi-class Supervised modelValueError when doing validation with random forestsClass weight degrades Multi Label Classification PerformanceTwo-class classification model with multi-type input dataHow to apply class weight to a multi-output model?Forcing a multi-label multi-class tree-based classifier to make more label predictions per documentUsing categorial_crossentropy to train a model in kerasHow Can I Solve it? TypeError: fillna() got an unexpected keyword argument 'implace'Unbalanced multi-label multi-class classification
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Multi-label compute class weight - unhashable type
2019 Community Moderator ElectionMulti-label Text ClassificationKMeans clustering to help label Multi-class Supervised modelValueError when doing validation with random forestsClass weight degrades Multi Label Classification PerformanceTwo-class classification model with multi-type input dataHow to apply class weight to a multi-output model?Forcing a multi-label multi-class tree-based classifier to make more label predictions per documentUsing categorial_crossentropy to train a model in kerasHow Can I Solve it? TypeError: fillna() got an unexpected keyword argument 'implace'Unbalanced multi-label multi-class classification
$begingroup$
Working in a multi-label classification problem with 13 possibles outputs in my neural network with Keras, sklearn, etc...
Each output can be an array like [0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1 ,0].
I have an imbalance dataset and i trying to apply compute_class_weight method, like:
class_weight = compute_class_weight('balanced', np.unique(Y_train), Y_train)
When i try to run my code, i got Unhashable Type: 'numpy.ndarray':
Traceback (most recent call last):
File "main.py", line 115, in <module>
train(dataset, labels)
File "main.py", line 66, in train
class_weight = compute_class_weight('balanced', np.unique(Y_train), Y_train)
File "/home/python-env/env/lib/python3.6/site-packages/sklearn/utils/class_weight.py", line 41, in compute_class_weight
if set(y) - set(classes):
TypeError: unhashable type: 'numpy.ndarray'
I know that is because i working with arrays, already tried add some dict,
i.e.:
class_weight_dict = dict(enumerate(np.unique(y_train), class_weight))
Well, i don't know what to do, tried others strategies, but no success... Any ideas?
Thanks in advance!
python neural-network keras scikit-learn
asked Feb 25 at 17:19
Alex ColombariAlex Colombari
111
$endgroup$
bumped to the homepage by Community♦ 28 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
Working in a multi-label classification problem with 13 possibles outputs in my neural network with Keras, sklearn, etc...
Each output can be an array like [0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1 ,0].
I have an imbalance dataset and i trying to apply compute_class_weight method, like:
class_weight = compute_class_weight('balanced', np.unique(Y_train), Y_train)
When i try to run my code, i got Unhashable Type: 'numpy.ndarray':
Traceback (most recent call last):
File "main.py", line 115, in <module>
train(dataset, labels)
File "main.py", line 66, in train
class_weight = compute_class_weight('balanced', np.unique(Y_train), Y_train)
File "/home/python-env/env/lib/python3.6/site-packages/sklearn/utils/class_weight.py", line 41, in compute_class_weight
if set(y) - set(classes):
TypeError: unhashable type: 'numpy.ndarray'
I know that is because i working with arrays, already tried add some dict,
i.e.:
class_weight_dict = dict(enumerate(np.unique(y_train), class_weight))
Well, i don't know what to do, tried others strategies, but no success... Any ideas?
Thanks in advance!
python neural-network keras scikit-learn
asked Feb 25 at 17:19
Alex ColombariAlex Colombari
111
$endgroup$
bumped to the homepage by Community♦ 28 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
Working in a multi-label classification problem with 13 possibles outputs in my neural network with Keras, sklearn, etc...
Each output can be an array like [0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1 ,0].
I have an imbalance dataset and i trying to apply compute_class_weight method, like:
class_weight = compute_class_weight('balanced', np.unique(Y_train), Y_train)
When i try to run my code, i got Unhashable Type: 'numpy.ndarray':
Traceback (most recent call last):
File "main.py", line 115, in <module>
train(dataset, labels)
File "main.py", line 66, in train
class_weight = compute_class_weight('balanced', np.unique(Y_train), Y_train)
File "/home/python-env/env/lib/python3.6/site-packages/sklearn/utils/class_weight.py", line 41, in compute_class_weight
if set(y) - set(classes):
TypeError: unhashable type: 'numpy.ndarray'
I know that is because i working with arrays, already tried add some dict,
i.e.:
class_weight_dict = dict(enumerate(np.unique(y_train), class_weight))
Well, i don't know what to do, tried others strategies, but no success... Any ideas?
Thanks in advance!
python neural-network keras scikit-learn
asked Feb 25 at 17:19
Alex ColombariAlex Colombari
111
$endgroup$
Working in a multi-label classification problem with 13 possibles outputs in my neural network with Keras, sklearn, etc...
Each output can be an array like [0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1 ,0].
I have an imbalance dataset and i trying to apply compute_class_weight method, like:
class_weight = compute_class_weight('balanced', np.unique(Y_train), Y_train)
When i try to run my code, i got Unhashable Type: 'numpy.ndarray':
Traceback (most recent call last):
File "main.py", line 115, in <module>
train(dataset, labels)
File "main.py", line 66, in train
class_weight = compute_class_weight('balanced', np.unique(Y_train), Y_train)
File "/home/python-env/env/lib/python3.6/site-packages/sklearn/utils/class_weight.py", line 41, in compute_class_weight
if set(y) - set(classes):
TypeError: unhashable type: 'numpy.ndarray'
I know that is because i working with arrays, already tried add some dict,
i.e.:
class_weight_dict = dict(enumerate(np.unique(y_train), class_weight))
Well, i don't know what to do, tried others strategies, but no success... Any ideas?
Thanks in advance!
python neural-network keras scikit-learn
python neural-network keras scikit-learn
asked Feb 25 at 17:19
Alex ColombariAlex Colombari
111
asked Feb 25 at 17:19
Alex ColombariAlex Colombari
111
asked Feb 25 at 17:19
Alex ColombariAlex Colombari
111
asked Feb 25 at 17:19
Alex ColombariAlex Colombari
111
asked Feb 25 at 17:19
Alex ColombariAlex Colombari
111
111
bumped to the homepage by Community♦ 28 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
bumped to the homepage by Community♦ 28 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
add a comment |
1 Answer
1
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$begingroup$
You're seeing this error because your Y_train data is a 2d array, where compute_class_weights expects a 1d array.
compute_class_weights can be used for multiclass classifications, but apparently not multi-label problems like yours.
You could try using compute_sample_weight instead, which is slightly different but handles multi-label output problems such as this.
answered Feb 25 at 19:24
Dan CarterDan Carter
7751218
$endgroup$
add a comment |
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1 Answer
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1 Answer
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$begingroup$
You're seeing this error because your Y_train data is a 2d array, where compute_class_weights expects a 1d array.
compute_class_weights can be used for multiclass classifications, but apparently not multi-label problems like yours.
You could try using compute_sample_weight instead, which is slightly different but handles multi-label output problems such as this.
answered Feb 25 at 19:24
Dan CarterDan Carter
7751218
$endgroup$
add a comment |
$begingroup$
You're seeing this error because your Y_train data is a 2d array, where compute_class_weights expects a 1d array.
compute_class_weights can be used for multiclass classifications, but apparently not multi-label problems like yours.
You could try using compute_sample_weight instead, which is slightly different but handles multi-label output problems such as this.
answered Feb 25 at 19:24
Dan CarterDan Carter
7751218
$endgroup$
add a comment |
$begingroup$
You're seeing this error because your Y_train data is a 2d array, where compute_class_weights expects a 1d array.
compute_class_weights can be used for multiclass classifications, but apparently not multi-label problems like yours.
You could try using compute_sample_weight instead, which is slightly different but handles multi-label output problems such as this.
answered Feb 25 at 19:24
Dan CarterDan Carter
7751218
$endgroup$
You're seeing this error because your Y_train data is a 2d array, where compute_class_weights expects a 1d array.
compute_class_weights can be used for multiclass classifications, but apparently not multi-label problems like yours.
You could try using compute_sample_weight instead, which is slightly different but handles multi-label output problems such as this.
answered Feb 25 at 19:24
Dan CarterDan Carter
7751218
answered Feb 25 at 19:24
Dan CarterDan Carter
7751218
answered Feb 25 at 19:24
Dan CarterDan Carter
7751218
answered Feb 25 at 19:24
Dan CarterDan Carter
7751218
7751218
add a comment |
add a comment |
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