Feature Selection Based on the Training Set Manipulation - PhD thesis proposal
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F05%3A00109895" target="_blank" >RIV/68407700:21230/05:00109895 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Feature Selection Based on the Training Set Manipulation - PhD thesis proposal
Original language 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.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA102%2F03%2F0440" target="_blank" >GA102/03/0440: Recognizing human activities for automated video surveillance</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2005
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů