HellingerHistogramNormalization 
Normalize histograms by scaling them to unit absolute sum, then taking the
square root of the absolute value in each attribute, times the normalization
constant \(1/\sqrt{2}\).

InstanceLogRankNormalization 
Normalize vectors such that the smallest value of each instance is 0, the
largest is 1, but using \( \log_2(1+x) \).

InstanceMeanVarianceNormalization 
Normalize vectors such that they have zero mean and unit variance.

InstanceMinMaxNormalization 
Normalize vectors with respect to a given minimum and maximum in each
dimension.

InstanceRankNormalization 
Normalize vectors such that the smallest value of each instance is 0, the
largest is 1.

LengthNormalization 
Class to perform a normalization on vectors to norm 1.

Log1PlusNormalization 
Normalize the data set by applying \( \frac{\log(1+xb)}{\log 1+b} \) to any
value.
