About: Feature Selection Based on the Training Set Manipulation

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

About: Feature Selection Based on the Training Set Manipulation - PhD thesis proposal 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	A novel feature selection technique for the classification problems is proposed in this PhD thesis proposal. The method is based on the training set manipulation. A weight is associated with each training sample similarly as it is in the AdaBoost algorithm. The weights form a distribution. Any change of the distribution of weights influences the behaviour of particular features in a different manner. This brings new information to the selection process in contrast to other feature selection techniques. The main idea is to modify the weights in each selection step so that the currently selected feature appears, with respect to the distribution, like an irrelevant observation. We show in experiments that such a change of the weights distribution allows to reveal hidden relationships between features. Although the feature selection algorithm is not completely developed yet, preliminary results achieved on several artificial problem looks promising. A novel feature selection technique for the classification problems is proposed in this PhD thesis proposal. The method is based on the training set manipulation. A weight is associated with each training sample similarly as it is in the AdaBoost algorithm. The weights form a distribution. Any change of the distribution of weights influences the behaviour of particular features in a different manner. This brings new information to the selection process in contrast to other feature selection techniques. The main idea is to modify the weights in each selection step so that the currently selected feature appears, with respect to the distribution, like an irrelevant observation. We show in experiments that such a change of the weights distribution allows to reveal hidden relationships between features. Although the feature selection algorithm is not completely developed yet, preliminary results achieved on several artificial problem looks promising. (en)
Title	Feature Selection Based on the Training Set Manipulation - PhD thesis proposal Feature Selection Based on the Training Set Manipulation - PhD thesis proposal (en)
skos:prefLabel	Feature Selection Based on the Training Set Manipulation - PhD thesis proposal Feature Selection Based on the Training Set Manipulation - PhD thesis proposal (en)
skos:notation	RIV/68407700:21230/05:00109895!RIV10-GA0-21230___
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(GA102/03/0440)
http://linked.open...vai/riv/dodaniDat	2010
http://linked.open...aciTvurceVysledku	Křížek, Pavel
http://linked.open.../riv/druhVysledku	O - Ostatní výsledky nezařaditelné do žádného z výše uvedených druhů výsledku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	České vysoké učení technické v Praze / Fakulta elektrotechnická
http://linked.open...dnocenehoVysledku	521474
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/05:00109895
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	AdaBoost; Feature selection (en)
http://linked.open.../riv/klicoveSlovo	AdaBoost Feature selection
http://linked.open...ontrolniKodProRIV	[FFA1F3D270A2]
http://linked.open...in/vavai/riv/obor	JD
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	1 (xsd:int)
http://linked.open...vavai/riv/projekt	Recognizing human activities for automated video surveillance
http://linked.open...UplatneniVysledku	2005
http://linked.open...iv/tvurceVysledku	Křížek, Pavel
http://localhost/t...ganizacniJednotka	21230

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, 58 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software