09 February 2018

🔬Data Science: Normalization (Definitions)

"Mathematical transformations to generate a new set of values that map onto a different range." (Glenn J Myatt, "Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining", 2006)

[Min–max normalization:] "Normalizing a variable value to a predetermine range." (Glenn J Myatt, "Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining", 2006)

[function point normalization:] "Dividing a metric by the project’s function points to allow you to compare projects of different sizes and complexities." (Rod Stephens, "Beginning Software Engineering", 2015)

"For metrics, performing some calculation on a metric to account for possible differences in project size or complexity. Two general approaches are size normalization and function point normalization." (Rod Stephens, "Beginning Software Engineering", 2015)

[size normalization:] "For metrics, dividing a metric by an indicator of size such as lines of code or days of work. For example, bugs/KLOC tells you how buggy the code is normalized for the size of the project." (Rod Stephens, "Beginning Software Engineering", 2015)


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