How to Normalise features for small datasets?












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I am working with a small dataset ( N = 50 ).
I would like to normalise my input features.
I am facing the following issues:




  1. Because of the small size of the dataset the range of training input features would differ from the range of testing input features.

  2. The input features do not have a theoretical upper bound.


Can you suggest normalisation techniques suitable for this task? Any paper suggestions would also be appreciated.









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    0












    $begingroup$


    I am working with a small dataset ( N = 50 ).
    I would like to normalise my input features.
    I am facing the following issues:




    1. Because of the small size of the dataset the range of training input features would differ from the range of testing input features.

    2. The input features do not have a theoretical upper bound.


    Can you suggest normalisation techniques suitable for this task? Any paper suggestions would also be appreciated.









    share







    New contributor




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







    $endgroup$















      0












      0








      0





      $begingroup$


      I am working with a small dataset ( N = 50 ).
      I would like to normalise my input features.
      I am facing the following issues:




      1. Because of the small size of the dataset the range of training input features would differ from the range of testing input features.

      2. The input features do not have a theoretical upper bound.


      Can you suggest normalisation techniques suitable for this task? Any paper suggestions would also be appreciated.









      share







      New contributor




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







      $endgroup$




      I am working with a small dataset ( N = 50 ).
      I would like to normalise my input features.
      I am facing the following issues:




      1. Because of the small size of the dataset the range of training input features would differ from the range of testing input features.

      2. The input features do not have a theoretical upper bound.


      Can you suggest normalisation techniques suitable for this task? Any paper suggestions would also be appreciated.







      machine-learning preprocessing





      share







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










      share







      New contributor




      Pranav Garg 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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      Pranav Garg is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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      asked 1 min ago









      Pranav GargPranav Garg

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