clustering with k means












0












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I have dataset with two label class (good and bad), I want to apply K Means on my dataset using python, should I use that label dataset or I have to delete the label class column ?






clustering







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  • 1




    $begingroup$
    K-means clustering is done to give labels to data. You already have those, so why are you applying k-means? What is the problem statement?
    $endgroup$
    – bkshi
    16 hours ago










  • $begingroup$
    I think the OP actually meant the dataset contains a binary feature.
    $endgroup$
    – Louis T
    16 hours ago










  • $begingroup$
    Possible duplicate of K-Means clustering for mixed numeric and categorical data
    $endgroup$
    – Louis T
    16 hours ago
















0












$begingroup$


I have dataset with two label class (good and bad), I want to apply K Means on my dataset using python, should I use that label dataset or I have to delete the label class column ?






clustering







share|improve this question









New contributor




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







$endgroup$








  • 1




    $begingroup$
    K-means clustering is done to give labels to data. You already have those, so why are you applying k-means? What is the problem statement?
    $endgroup$
    – bkshi
    16 hours ago










  • $begingroup$
    I think the OP actually meant the dataset contains a binary feature.
    $endgroup$
    – Louis T
    16 hours ago










  • $begingroup$
    Possible duplicate of K-Means clustering for mixed numeric and categorical data
    $endgroup$
    – Louis T
    16 hours ago














0












0








0





$begingroup$


I have dataset with two label class (good and bad), I want to apply K Means on my dataset using python, should I use that label dataset or I have to delete the label class column ?






clustering







share|improve this question









New contributor




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







$endgroup$




I have dataset with two label class (good and bad), I want to apply K Means on my dataset using python, should I use that label dataset or I have to delete the label class column ?






clustering




clustering






share|improve this question









New contributor




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











share|improve this question









New contributor




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









share|improve this question




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edited 8 hours ago









Anony-Mousse

4,750624




4,750624






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asked 18 hours ago









lonalona

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





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






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








  • 1




    $begingroup$
    K-means clustering is done to give labels to data. You already have those, so why are you applying k-means? What is the problem statement?
    $endgroup$
    – bkshi
    16 hours ago










  • $begingroup$
    I think the OP actually meant the dataset contains a binary feature.
    $endgroup$
    – Louis T
    16 hours ago










  • $begingroup$
    Possible duplicate of K-Means clustering for mixed numeric and categorical data
    $endgroup$
    – Louis T
    16 hours ago














  • 1




    $begingroup$
    K-means clustering is done to give labels to data. You already have those, so why are you applying k-means? What is the problem statement?
    $endgroup$
    – bkshi
    16 hours ago










  • $begingroup$
    I think the OP actually meant the dataset contains a binary feature.
    $endgroup$
    – Louis T
    16 hours ago










  • $begingroup$
    Possible duplicate of K-Means clustering for mixed numeric and categorical data
    $endgroup$
    – Louis T
    16 hours ago








1




1




$begingroup$
K-means clustering is done to give labels to data. You already have those, so why are you applying k-means? What is the problem statement?
$endgroup$
– bkshi
16 hours ago




$begingroup$
K-means clustering is done to give labels to data. You already have those, so why are you applying k-means? What is the problem statement?
$endgroup$
– bkshi
16 hours ago












$begingroup$
I think the OP actually meant the dataset contains a binary feature.
$endgroup$
– Louis T
16 hours ago




$begingroup$
I think the OP actually meant the dataset contains a binary feature.
$endgroup$
– Louis T
16 hours ago












$begingroup$
Possible duplicate of K-Means clustering for mixed numeric and categorical data
$endgroup$
– Louis T
16 hours ago




$begingroup$
Possible duplicate of K-Means clustering for mixed numeric and categorical data
$endgroup$
– Louis T
16 hours ago










1 Answer
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$begingroup$

Delete the label column.



Assuming that you want to compare the clusters to the labels later, then the labels must not be part of the data passed to k-means.



And k-means only works well on continuous variables anyway.






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    0












    $begingroup$

    Delete the label column.



    Assuming that you want to compare the clusters to the labels later, then the labels must not be part of the data passed to k-means.



    And k-means only works well on continuous variables anyway.






    share|improve this answer









    $endgroup$


















      0












      $begingroup$

      Delete the label column.



      Assuming that you want to compare the clusters to the labels later, then the labels must not be part of the data passed to k-means.



      And k-means only works well on continuous variables anyway.






      share|improve this answer









      $endgroup$
















        0












        0








        0





        $begingroup$

        Delete the label column.



        Assuming that you want to compare the clusters to the labels later, then the labels must not be part of the data passed to k-means.



        And k-means only works well on continuous variables anyway.






        share|improve this answer









        $endgroup$



        Delete the label column.



        Assuming that you want to compare the clusters to the labels later, then the labels must not be part of the data passed to k-means.



        And k-means only works well on continuous variables anyway.







        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered 8 hours ago









        Anony-MousseAnony-Mousse

        4,750624




        4,750624






















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