Min-Max Scaling

data-analysis

Definition

Min-Max Scaling

Min-Max-Scaling is a data preprocessing method used to rescale numerical data to a fixed range, e.g. or .

Let be the data space. Each value of a data point at dimension , i.e., , is scaled such that it fits into the specific range of .

For range :

For range :

Transformation Characteristics

While min-max scaling preserves the relative distances between values, it is highly sensitive to outliers, as a single extreme value can significantly influence the and statistics, thereby compressing the majority of the data into a very narrow range.

Definition

Independent Feature Scaling

Independent feature scaling is the principle that statistical scaling operations must be applied individually to each feature dimension of a dataset. Formally, for a dataset with , the scaling parameters (e.g., ) are computed for each dimension independently:

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