How to Normalise features for small datasets?
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:
- Because of the small size of the dataset the range of training input features would differ from the range of testing input features.
- 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
asked 11 mins ago
Pranav GargPranav Garg
1
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$endgroup$
add a comment |
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:
- Because of the small size of the dataset the range of training input features would differ from the range of testing input features.
- 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
asked 11 mins ago
Pranav GargPranav Garg
1
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.
$endgroup$
add a comment |
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:
- Because of the small size of the dataset the range of training input features would differ from the range of testing input features.
- 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
asked 11 mins ago
Pranav GargPranav Garg
1
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:
- Because of the small size of the dataset the range of training input features would differ from the range of testing input features.
- 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
machine-learning preprocessing
asked 11 mins ago
Pranav GargPranav Garg
1
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.
asked 11 mins ago
Pranav GargPranav Garg
1
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.
asked 11 mins ago
Pranav GargPranav Garg
1
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.
asked 11 mins ago
Pranav GargPranav Garg
1
asked 11 mins ago
Pranav GargPranav Garg
1
1
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.
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.
Pranav Garg is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
add a comment |
add a comment |
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