when normalising higher moments in features why do you normalise features can machine learning skewness and kurtosis be normalized? why is machine learning used as a feature vector do you normalise a feature vector why do machine learning features have higher mean when normalising feature vectors why are feature vectors usually normalised what is normalising higher moments why are features prone to change? why do I normally use features to normalise higher moments how to use different feature vectors in machine learning what is the normalization of higher moments mean how does the machine learn feature vector work what does it mean to normalise a feature vector for machine learning what is normalising higher moments why do we normalise higher moments of feature vectors which features are normally normalised in feature vectors why is it important to normalising the moments of features why do you normalise features?