Outlier-robust feature scaling
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Dear All,
What feature scaling method would you recommend to bring data within [0 1] or [-1 1], for features that are heavily skewed /non nonnormal (t location scale, generalized extreme value distros), and for which outliers are preferably not removed (features are i1-i2 image subtractions that use outliers in classification, some also have different units).
Thank you,
OL
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