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pro vyhledávání: '"Kłopotek, Mieczysław A."'
Our previous experiments demonstrated that subsets collections of (short) documents (with several hundred entries) share a common normalized in some way eigenvalue spectrum of combinatorial Laplacian. Based on this insight, we propose a method of inc
Externí odkaz:
http://arxiv.org/abs/2308.10999
Autor:
Kłopotek, Mieczysław A.
The widely applied k-means algorithm produces clusterings that violate our expectations with respect to high/low similarity/density and is in conflict with Kleinberg's axiomatic system for distance based clustering algorithms that formalizes those ex
Externí odkaz:
http://arxiv.org/abs/2308.03464
Autor:
Kłopotek, Mieczysław A.
This paper investigates the capability of correctly recovering well-separated clusters by various brands of the $k$-means algorithm. The concept of well-separatedness used here is derived directly from the common definition of clusters, which imposes
Externí odkaz:
http://arxiv.org/abs/2308.01926
Spectral clustering methods are known for their ability to represent clusters of diverse shapes, densities etc. However, results of such algorithms, when applied e.g. to text documents, are hard to explain to the user, especially due to embedding in
Externí odkaz:
http://arxiv.org/abs/2308.00504
Autor:
Kłopotek, Mieczysław A.
Kleinberg's axioms for distance based clustering proved to be contradictory. Various efforts have been made to overcome this problem. Here we make an attempt to handle the issue by embedding in high-dimensional space and granting wide gaps between cl
Externí odkaz:
http://arxiv.org/abs/2211.17036
The paper points at the grieving problems implied by the richness axiom in the Kleinberg's axiomatic system and suggests resolutions. The richness induces learnability problem in general and leads to conflicts with consistency axiom. As a resolution,
Externí odkaz:
http://arxiv.org/abs/2210.15507
Autor:
Kłopotek Mieczysław A.
Publikováno v:
International Journal of Applied Mathematics and Computer Science, Vol 34, Iss 1, Pp 135-147 (2024)
The widely applied k-means algorithm produces clusterings that violate our expectations with respect to high/low similarity/density within/between clusters and is in conflict with Kleinberg’s axiomatic system for distance based clustering algorithm
Externí odkaz:
https://doaj.org/article/5459fce7faf4471e9b5936dd24e2052f
Autor:
Kłopotek, Mieczysław A.
This note introduces a novel clustering preserving transformation of cluster sets obtained from $k$-means algorithm. This transformation may be used to generate new labeled data{}sets from existent ones. It is more flexible that Kleinberg axiom based
Externí odkaz:
http://arxiv.org/abs/2202.10455
Publikováno v:
Applied Intelligence 2022
Development of new algorithms in the area of machine learning, especially clustering, comparative studies of such algorithms as well as testing according to software engineering principles requires availability of labeled data sets. While standard be
Externí odkaz:
http://arxiv.org/abs/2202.06015
Autor:
Kłopotek, Mieczysław A.
Spirtes, Glymour and Scheines formulated a Conjecture that a direct dependence test and a head-to-head meeting test would suffice to construe directed acyclic graph decompositions of a joint probability distribution (Bayesian network) for which Pearl
Externí odkaz:
http://arxiv.org/abs/2006.09196