Clustering and classification of multi-label data












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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.









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    $begingroup$


    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.









    share







    New contributor




    Yogesch is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.







    $endgroup$















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      $begingroup$


      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.









      share







      New contributor




      Yogesch is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.







      $endgroup$




      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





      share







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      Yogesch is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.










      share







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      Yogesch is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.








      share



      share






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      Yogesch is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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      asked 2 mins ago









      YogeschYogesch

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      Yogesch is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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      New contributor





      Yogesch is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.






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