In the QuickNet package, there is a tool called qnnorm, which could be used to go through all the data and compute a normalization file.%20*%20v_i)
IN the normalization file, two vectors are stored:
1) Mean vector - mean values for each dimension;
2) Diagonal Covariance vector - diagonal values of the covariance matrix;
Thus for each dimension of the feature vector f, the normalized value is:
where fi is the original feature value, mi is the corresponding mean and vi is the corresponding diagonal covariance value.
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