kmvalidate: Validate a knowledge structure against a data set

In kstMatrix: Basic Functions in Knowledge Space Theory Using Matrix Representation

Validate a knowledge structure against a data set

Description

kmvalidate returns a list with three elements, a named vector with the frequencies of distances between a set of response patterns and a knowledge structure, the Discrepancy Index (DI), and the Distance Agreement Coefficient (DA).

Usage

kmvalidate(data, struct)

Arguments

data	Binary matrix representing a set of response patterns
struct	Binary matrix representing a knowledge structure

Value

A list with three elements:

dist

Distance distribution vector

DI

Discrepancy Index

DA

Distance Agreement Coefficient

Warning

The DA computation can take quite some time for larger item sets as the power set has to be computed. For item sets with around 30 items or more, it may even crash the system due to huge memory requests.

See Also

Other Validating knowledge spaces: kmdist()

Examples

kmvalidate(xpl$data, xpl$space)

kstMatrix documentation built on Oct. 4, 2024, 1:08 a.m.