Clustering and classification of multi-label data
$begingroup$
The dataset consists of 1) a set of objects and 2) a set of labels, which are used to describe the objects.
For the moment, for simplicity sake, each label can be marked as either true or false (In a more complex setup, each label will have a value of 1-10).
But, not all the labels are actually applied to all the objects (in principle, all the labels can and should be applied across all the objects, but in practice, they just are not). Also, when a label isn't applied to an object, one cannot simply assume that the label's value for that particular is false.
I need to cluster and classify the objects based on their labels. Any tips on how and what algorithms to use will be appreciated.
I just made this datascience.se account, so any comments on if/how the question can be improved can be helpful.
classification clustering multilabel-classification labels
New contributor
$endgroup$
add a comment |
$begingroup$
The dataset consists of 1) a set of objects and 2) a set of labels, which are used to describe the objects.
For the moment, for simplicity sake, each label can be marked as either true or false (In a more complex setup, each label will have a value of 1-10).
But, not all the labels are actually applied to all the objects (in principle, all the labels can and should be applied across all the objects, but in practice, they just are not). Also, when a label isn't applied to an object, one cannot simply assume that the label's value for that particular is false.
I need to cluster and classify the objects based on their labels. Any tips on how and what algorithms to use will be appreciated.
I just made this datascience.se account, so any comments on if/how the question can be improved can be helpful.
classification clustering multilabel-classification labels
New contributor
$endgroup$
add a comment |
$begingroup$
The dataset consists of 1) a set of objects and 2) a set of labels, which are used to describe the objects.
For the moment, for simplicity sake, each label can be marked as either true or false (In a more complex setup, each label will have a value of 1-10).
But, not all the labels are actually applied to all the objects (in principle, all the labels can and should be applied across all the objects, but in practice, they just are not). Also, when a label isn't applied to an object, one cannot simply assume that the label's value for that particular is false.
I need to cluster and classify the objects based on their labels. Any tips on how and what algorithms to use will be appreciated.
I just made this datascience.se account, so any comments on if/how the question can be improved can be helpful.
classification clustering multilabel-classification labels
New contributor
$endgroup$
The dataset consists of 1) a set of objects and 2) a set of labels, which are used to describe the objects.
For the moment, for simplicity sake, each label can be marked as either true or false (In a more complex setup, each label will have a value of 1-10).
But, not all the labels are actually applied to all the objects (in principle, all the labels can and should be applied across all the objects, but in practice, they just are not). Also, when a label isn't applied to an object, one cannot simply assume that the label's value for that particular is false.
I need to cluster and classify the objects based on their labels. Any tips on how and what algorithms to use will be appreciated.
I just made this datascience.se account, so any comments on if/how the question can be improved can be helpful.
classification clustering multilabel-classification labels
classification clustering multilabel-classification labels
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YogeschYogesch
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Yogesch is a new contributor. Be nice, and check out our Code of Conduct.
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