Kirjeldavfunctions

Kirjeldavfunctions is a term used in information science and mathematics to refer to a class of functions that produce descriptive summaries of data and objects rather than predictive or transformative outputs. The concept centers on describing observed properties, relationships, and structures to convey understanding of a dataset or system.

Formal definition and scope

A descriptive function can be viewed as a mapping f from a domain X to a descriptor space D, where f(x) encodes measurable characteristics of x. Descriptors may be scalars, vectors, or symbolic representations and can include central tendency, dispersion, distributional shape, dimensionality, frequency, or topological features. In practice, a descriptive function often outputs a compact summary suitable for reporting, profiling, or visualization.

Examples

Common descriptive functions include statistical descriptors such as mean, median, mode, standard deviation, interquartile range, skewness, and excess kurtosis; quantiles and percentiles; counts of elements and missing values; dimensionality measures; density estimates; and simple textual or graphical summaries. In data pipelines, descriptive functions may generate reports, dashboards, or metadata about datasets and processes.

Relation to other concepts

Descriptive functions are typically contrasted with predictive or prescriptive functions, as they aim to summarize or characterize existing data rather than infer future values or prescribe actions. They often appear within exploratory data analysis, data profiling, feature extraction, and summarization workflows, and can be deterministic or incorporate sampling.

Usage and notes

The term kirjeldevfunctions is not widely standardized and may vary in meaning across disciplines. In educational and theoretical contexts, it is used to denote the broad family of operations that describe data properties, serving as a foundation for descriptive statistics, reporting, and data quality assessment.