calcContinuityFromDist: Calculate continuity based on distance matrices

In csoneson/dreval: Evaluate Reduced Dimension Representations

Calculate continuity based on distance matrices

Description

The continuity was proposed by Venna and Kaski, as a local quality measure of a low-dimensional representation. The metric focuses on the preservation of local neighborhoods, and compares the neighborhoods of points in the low-dimensional representation to those in the reference data. Hence, the continuity measure indicates to which degree we can trust that the points closest to a given sample in the reference data set are placed close to the sample also in the low-dimensional representation. The kTM parameter defines the size of the neighborhoods to consider.

Usage

calcContinuityFromDist(distReference, distLowDim, kTM)

Arguments

distReference	N x N matrix or dist object, representing pairwise sample distances based on the reference (high-dimensional) observed values. For each column, samples (rows) will be ranked by the provided distances.
kTM	The number of nearest neighbors (excluding the sample itself).
rankLowDim	N x N matrix or dist object, representing pairwise sample distances based on the low-dimensional representation. For each column, samples (rows) will be ranked by the provided distances.

Value

The continuity value.

Author(s)

Charlotte Soneson

References

Venna J., Kaski S. (2001). Neighborhood preservation in nonlinear projection methods: An experimental study. In Dorffner G., Bischof H., Hornik K., editors, Proceedings of ICANN 2001, pp 485–491. Springer, Berlin.

csoneson/dreval documentation built on Jan. 26, 2024, 6:32 p.m.