Regression analysis with cluster ensemble and kernel function

Vladimir Berikov, Taisiya Vinogradova

Результат исследования: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаярецензирование

2 Цитирования (Scopus)


In this paper, we consider semi-supervised regression problem. The proposed method can be divided into two steps. In the first step, a number of variants of clustering partition are obtained with some clustering algorithm working on both labeled and unlabeled data. Weighted co-association matrix is calculated using the results of partitioning. It is known that this matrix satisfies Mercer’s condition, so it can be used as a kernel for a kernel-based regression algorithm. In the second step, we use the obtained matrix as kernel to construct the decision function based on labelled data. With the use of probabilistic model, we prove that the probability that the error is significant converges to its minimum possible value as the number of elements in the cluster ensemble tends to infinity. Output of the method applied to a real set of data is compared with the results of popular regression methods that use a standard kernel and have all the data labelled. In noisy conditions the proposed method showed higher quality, compared with support vector regression algorithm with standard kernel.

Язык оригиналаанглийский
Название основной публикацииAnalysis of Images, Social Networks and Texts - 7th International Conference, AIST 2018, Revised Selected Papers
РедакторыAlexander Panchenko, Wil M. van der Aalst, Michael Khachay, Panos M. Pardalos, Vladimir Batagelj, Natalia Loukachevitch, Goran Glavaš, Dmitry I. Ignatov, Sergei O. Kuznetsov, Olessia Koltsova, Irina A. Lomazova, Andrey V. Savchenko, Amedeo Napoli, Marcello Pelillo
ИздательSpringer-Verlag GmbH and Co. KG
Число страниц10
ISBN (печатное издание)9783030110260
СостояниеОпубликовано - 1 янв 2018
Событие7th International Conference on Analysis of Images, Social Networks and Texts, AIST 2018 - Moscow, Российская Федерация
Продолжительность: 5 июл 20187 июл 2018

Серия публикаций

НазваниеLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Том11179 LNCS
ISSN (печатное издание)0302-9743
ISSN (электронное издание)1611-3349


Конференция7th International Conference on Analysis of Images, Social Networks and Texts, AIST 2018
СтранаРоссийская Федерация


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