element of row=(element of row-mean(of column))/standard deviation (if same col).
1. Delete and/or modify numerical outliers. Standardization of data to zero-mean/unit-variance is the most effective way to do this. 2. Keep the ranges of all input and target vector components comparable to help understand their relative importance. 3. Consider biases to be weights that act on unit vector components 4. Keep the initial scalar products of weights and vectors within the linear regions of the sigmoids to avoid algebraic stagnation in the asymptotic regions. 5. Data scaling to [-1 1 ] is a MATLAB default. Standardization and no scaling are the alternatives. Since you already have unscaled and standardarized data, you have a variety of choices. My choice is to use the standardized data but accept the [-1 1 ] default.
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