In the context of data analysis and data mining: Where “V” represents the value of the variable in the original datasets: Transformation of data to have zero mean and unit variance. Techniques used include: (a) Data normalization; (b) z-score scaling; (c) Dividing each value by the range: recalculates each variable as V /(max V – min V). In this case, the means, variances, and ranges of the variables are still different, but at least the ranges are likely to be more similar; and, (d) Dividing each value by the standard deviation. This method produces a set of transformed variables with variances of 1, but different means and ranges. RELATED TERM. Data normalization; Data z-score normalization
