Data normalization using robust scaling
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Hello all, I am trying to implement "Robust Scaling" but I am confused. Should I use "all" argument for "median" and "iqr" functions?
Thanks for the help.
DataSet = readtable('Datasets/Test.csv');
DataSet = table2array(DataSet); % Row:7195 x Colums:22
RScaling = (DataSet - median(DataSet))./iqr(DataSet)
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Voss
2024년 6월 4일
1 개 추천
If you want to normalize all columns the same way (i.e., using the median and inter-quartile range of the entire data set), then use "all".
If you want to normalize each column separately (i.e., using each column's own median and inter-quartile range), then do not use "all". And in this case, it's best to use the dim argument set to 1, to explicitly say you want the median and iqr by column, in order to properly handle the situation that your data set has only one row.
댓글 수: 4
You're welcome!
"If I understand correctly, this normalizes each column separately. "If A is a matrix, then normalize operates on each column of A separately.""
That's right. For a matrix that's not a vector, the default dim is 1, so you don't have to specify it (but it doesn't hurt to specify it). However, if you ever had the situation where your data set had one row, then you would need to specify dim as 1 if you want to normalize by column. Therefore, it's a good idea to always include the dim as 1. That's all I was suggesting.
Example: Matrix:
data = [1 2 3; 4 5 6] % non-vector matrix
normalize(data) % normalize each column
normalize(data,1) % same
normalize(data,2) % normalize each row
Row vector (matrix with one row):
data = [1 2 3] % row vector
normalize(data) % without the dim specified, this normalizes all together this time
normalize(data,1) % normalize each column
normalize(data,2) % normalize each row (same as all together in this case)
MB
2024년 6월 4일
Voss
2024년 6월 4일
You're welcome!
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