About: Ordinal Classification with Monotonicity Constraints

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Ordinal Classification with Monotonicity Constraints Goto Sponge NotDistinct Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	Classification methods commonly assume unordered class values. In many practical applications – for example grading – there is a natural ordering between class values. Furthermore, some attribute values of classified objects can be ordered, too. The standard approach in this case is to convert the ordered values into a numeric quantity and apply a regression learner to the transformed data. This approach can be used just in case of linear ordering. The proposed method for such a classification lies on the boundary between ordinal classification trees, classification trees with monotonicity constraints and multi-relational classification trees. The advantage of the proposed method is that it is able to handle non-linear ordering on the class and attribute values. For the better understanding, we use a toy example from the semantic web environment - prediction of rules for the user’s evaluation of hotels. Classification methods commonly assume unordered class values. In many practical applications – for example grading – there is a natural ordering between class values. Furthermore, some attribute values of classified objects can be ordered, too. The standard approach in this case is to convert the ordered values into a numeric quantity and apply a regression learner to the transformed data. This approach can be used just in case of linear ordering. The proposed method for such a classification lies on the boundary between ordinal classification trees, classification trees with monotonicity constraints and multi-relational classification trees. The advantage of the proposed method is that it is able to handle non-linear ordering on the class and attribute values. For the better understanding, we use a toy example from the semantic web environment - prediction of rules for the user’s evaluation of hotels. (en) Klasifikační metody obvykle předpokládají neuspořádané třídy hodnot klasifikace. V praktických příkladech (např. známkování) máme přirozené uspořádaní mezi klasifikačními hodnotami. Námi navržená metoda ordinální klasifikace leží na pomezi ordinálními klasifikačními stromy, klasifikačními stromy s omezeními na monotonii a více-relačními klasifikačními stromy. Výhodou navržené metody je, že může pracovat i s nelineárním uspořádáním klasifikačních hodnot. (cs)
Title	Ordinal Classification with Monotonicity Constraints Ordinální klasifikace s monotónními omezeními (cs) Ordinal Classification with Monotonicity Constraints (en)
skos:prefLabel	Ordinal Classification with Monotonicity Constraints Ordinální klasifikace s monotónními omezeními (cs) Ordinal Classification with Monotonicity Constraints (en)
skos:notation	RIV/67985807:_____/06:00096927!RIV08-AV0-67985807
http://linked.open.../vavai/riv/strany	217;225
http://linked.open...avai/riv/aktivita	P Z
http://linked.open...avai/riv/aktivity	P(1ET100300517), Z(AV0Z10300504)
http://linked.open...vai/riv/dodaniDat	2008
http://linked.open...aciTvurceVysledku	Vojtáš, Peter
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Ústav informatiky AV ČR, v. v. i.
http://linked.open...dnocenehoVysledku	490984
http://linked.open...ai/riv/idVysledku	RIV/67985807:_____/06:00096927
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	monotone; monotonicity constraints; classification; ordinal data (en)
http://linked.open.../riv/klicoveSlovo	classification ordinal data monotone monotonicity constraints
http://linked.open...ontrolniKodProRIV	[4975D0EE8F97]
http://linked.open...v/mistoKonaniAkce	Leipzig
http://linked.open...i/riv/mistoVydani	Berlin
http://linked.open...i/riv/nazevZdroje	Advances in Data Mining. Applications in Medicine, Web Mining, Marketing, Image and Signal Mining
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (xsd:int)
http://linked.open...vavai/riv/projekt	Methods for Intelligent Systems and Their Applications in Datamining and Natural Language Processing
http://linked.open...UplatneniVysledku	2006
http://linked.open...iv/tvurceVysledku	Vojtáš, Peter Horváth, T.
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2006-07-14 (xsd:date)
http://linked.open...n/vavai/riv/zamer	Informatika pro informační společnost: modely, algoritmy, aplikace
number of pages	9 (xsd:int)
http://purl.org/ne...btex#hasPublisher	Springer-Verlag
https://schema.org/isbn	978-3-540-36036-0

Faceted Search & Find service v1.16.118 as of Jun 21 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 67 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software