Pith. sign in

REVIEW

Top-down induction of clustering trees

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv cs/0011032 v1 pith:UXSJ4YSU submitted 2000-11-21 cs.LG

Top-down induction of clustering trees

classification cs.LG
keywords clusteringinductionsystemtreesdecisionemploysfirstorder
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

An approach to clustering is presented that adapts the basic top-down induction of decision trees method towards clustering. To this aim, it employs the principles of instance based learning. The resulting methodology is implemented in the TIC (Top down Induction of Clustering trees) system for first order clustering. The TIC system employs the first order logical decision tree representation of the inductive logic programming system Tilde. Various experiments with TIC are presented, in both propositional and relational domains.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.