Classification trees in a box extent lattice

TL;DR

This paper presents a method for updating classification trees in box extent lattices efficiently during context extensions, requiring minimal additional information.

Contribution

It introduces an algorithm to modify existing classification trees for extended contexts, avoiding complete recomputation.

Findings

The algorithm effectively updates classification trees with minimal data.

It simplifies the process of extending box extent lattices.

The method reduces computational effort in lattice extensions.

Abstract

In this paper we show that during an elementary extension of a context each of the classification trees of the newly created box extent lattice can be obtained by the modification of the classification trees of the box extent lattice of the original, smaller context. We construct also an algorithm which, starting from a classification tree of the box extent lattice of the smaller context $(H,M,I\cap H\times M),$ gives a classification tree of the extended context $(G,M,I)$ which contains the new elements inserted. The effectiveness of the method is that it ensures that there is enough to know the original context, the classification tree of the box extent lattice and its box extents, we do not need a new box extension of the extended context mesh elements (except for one, which is the new element box extension).