Expert-gate algorithm Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/h415pd31h

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  • The goal of Inductive Learning is to produce general rules from a set of seen examples, which can then be applied to other unseen examples. ID3 is an inductive learning algorithm that can be used for the classification task. The input to the algorithm is a set of tuples of description and class. The ID3 algorithm learns a decision tree from these input examples, which can then be used for classifying unseen examples given their descriptions. ID3 faces a problem called the replication problem. An algorithm called the Expert-Gate algorithm is presented in this thesis. The aim of the algorithm is to tackle the replication problem. We discuss the various issues involved with each step of the algorithm and present results corroborating our choices. The algorithm was tested on various artificially created problems as well as on a real life problem. The performance of the algorithm was compared with that of Fringe. The algorithm was found to give excellent results on the artificially created problems. The Expert-Gate algorithm gave satisfactory results on the NETtalk problem. Overall, we believe the algorithm is a good candidate for testing on other real life domains.
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  • File scanned at 300 ppi (Monochrome) using Capture Perfect 3.0 on a Canon DR-9050C in PDF format. CVista PdfCompressor 4.0 was used for pdf compression and textual OCR.
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  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2013-01-23T15:20:09Z (GMT) No. of bitstreams: 1 JoshiVaradVidyadhar1993.pdf: 1913358 bytes, checksum: b329b5870d9f44fc0e1038855ff1c4ed (MD5)
  • description.provenance : Made available in DSpace on 2013-01-23T15:20:09Z (GMT). No. of bitstreams: 1 JoshiVaradVidyadhar1993.pdf: 1913358 bytes, checksum: b329b5870d9f44fc0e1038855ff1c4ed (MD5) Previous issue date: 1992-11-23
  • description.provenance : Submitted by Kirsten Clark (kcscannerosu@gmail.com) on 2012-12-26T21:58:25Z No. of bitstreams: 1 JoshiVaradVidyadhar1993.pdf: 1873535 bytes, checksum: 619d80457374269913fd8a0c792a3b69 (MD5)
  • description.provenance : Submitted by Kirsten Clark (kcscannerosu@gmail.com) on 2013-01-22T17:19:28Z No. of bitstreams: 1 JoshiVaradVidyadhar1993.pdf: 1913358 bytes, checksum: b329b5870d9f44fc0e1038855ff1c4ed (MD5)
  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2012-12-26T22:59:04Z (GMT) No. of bitstreams: 1 JoshiVaradVidyadhar1993.pdf: 1873535 bytes, checksum: 619d80457374269913fd8a0c792a3b69 (MD5)
  • description.provenance : Rejected by Patricia Black(patricia.black@oregonstate.edu), reason: Redact signatures on 2013-01-22T16:12:19Z (GMT)
  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2013-01-22T18:31:40Z (GMT) No. of bitstreams: 1 JoshiVaradVidyadhar1993.pdf: 1913358 bytes, checksum: b329b5870d9f44fc0e1038855ff1c4ed (MD5)

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