Fenner, Mark E
(2008)
Semantic Feature Construction.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
An effective set of features is integral to the success of machine learning algorithms. Semantic feature construction is the knowledge-driven manipulation of the propositional descriptor space of a set of examples for use in a learning algorithm. Two important sources of semanticsfor feature construction are the semantic type (and associated semantic properties) and the semantic class of features. These semantics canbe captured in a knowledge base and utilized to constrain search through the space of constructed features. This dissertation presents a systemthat captures semantic feature construction knowledge and implements a search algorithm that respects that knowledge. Results are presentedfor different combinations of features generated from different successor functions used in search. These results are compiled over many learning problems and several learning algorithms. Other results are also presentedfor different levels of detail in semantic knowledge. Generally, semantics are an effective guide in the space of constructed features.
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Details
Item Type: |
University of Pittsburgh ETD
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Status: |
Unpublished |
Creators/Authors: |
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ETD Committee: |
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Date: |
24 January 2008 |
Date Type: |
Completion |
Defense Date: |
14 June 2007 |
Approval Date: |
24 January 2008 |
Submission Date: |
6 August 2007 |
Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
Institution: |
University of Pittsburgh |
Schools and Programs: |
Dietrich School of Arts and Sciences > Computer Science |
Degree: |
PhD - Doctor of Philosophy |
Thesis Type: |
Doctoral Dissertation |
Refereed: |
Yes |
Uncontrolled Keywords: |
constructive induction; domain knowledge |
Other ID: |
http://etd.library.pitt.edu/ETD/available/etd-08062007-175343/, etd-08062007-175343 |
Date Deposited: |
10 Nov 2011 19:57 |
Last Modified: |
15 Nov 2016 13:48 |
URI: |
http://d-scholarship.pitt.edu/id/eprint/8936 |
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