Many real data sets contain numerical features (variables) whose distribution is far from normal (gaussian). Instead, their often skewed. In order to handle such it customary preprocess the variables make them more normal. The Box-Cox and Yeo-Johnson transformations are well-known tools for this. However, standard maximum likelihood estimator of transformation parameter highly sensitive outlier...