featuresvolume
Featuresvolume is a term used in data analysis to denote a summary of how much of the feature space is utilized by a dataset or representation. It is a scalar intended to reflect the spread or diversity of features after preprocessing. Because feature space is defined by the chosen features, featuresvolume depends on the feature set, scaling, and dimensionality.
Several definitions are used in practice. One common approach is the volume of the convex hull of
Applications include assessing feature diversity, comparing feature extraction pipelines, and monitoring changes during feature engineering or
Limitations include sensitivity to outliers, dependence on scaling and feature selection, and the curse of dimensionality
See also: feature space, dimensionality, convex hull, generalized variance, covariance matrix, feature engineering.