INTERACTIVE SYSTEM FOR THE DESIGN OF CLASSIFIERS IN DIAGNOSTIC APPLICATIONS.

Sholom M. Weiss, Kevin B. Kern, Casimir Kulikowski, William Pincus

Research output: Contribution to conferencePaper

Abstract

A computer system has been developed for the interactive design of pattern classifiers. The purpose of this system is to allow the researcher to interact with a data base of samples and incrementally design practical pattern recognizers, particularly for diagnostic applications. In this system, several well-known methods have been implemented, such as: Bayes' rule with independence and with 1st order dependence, and the K-nearest neighbor method. Adjustments can be made to the methods and the data base such that: only a subset of the features may be considered, decision boundaries varied, and misclassified patterns displayed. Frequencies and probability estimates for combinations of patterns of features are generated from the data base. In some cases, this leads to an effective alternative to the pattern recognition methods cited above. With a sufficiently large data base and a relatively small subset of features, complete dependence among features can sometimes be extracted. Probability estimates can be generated for combinations of patterns which cover all mutually exclusive possibilities. The design of a classifier is described which evaluates the prognosis of patients with bronchial asthma who are being considered for immunotherapy.

Original languageEnglish (US)
Pages58-62
Number of pages5
StatePublished - Jan 1 1978
EventProc Int Conf Cybern Soc Tokyo, Jpn, Nov 3-5 - Kyoto, Jpn
Duration: Nov 7 1978Nov 7 1978

Other

OtherProc Int Conf Cybern Soc Tokyo, Jpn, Nov 3-5
CityKyoto, Jpn
Period11/7/7811/7/78

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Classifiers
Pattern recognition
Computer systems

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Weiss, S. M., Kern, K. B., Kulikowski, C., & Pincus, W. (1978). INTERACTIVE SYSTEM FOR THE DESIGN OF CLASSIFIERS IN DIAGNOSTIC APPLICATIONS.. 58-62. Paper presented at Proc Int Conf Cybern Soc Tokyo, Jpn, Nov 3-5, Kyoto, Jpn, .
Weiss, Sholom M. ; Kern, Kevin B. ; Kulikowski, Casimir ; Pincus, William. / INTERACTIVE SYSTEM FOR THE DESIGN OF CLASSIFIERS IN DIAGNOSTIC APPLICATIONS. Paper presented at Proc Int Conf Cybern Soc Tokyo, Jpn, Nov 3-5, Kyoto, Jpn, .5 p.
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abstract = "A computer system has been developed for the interactive design of pattern classifiers. The purpose of this system is to allow the researcher to interact with a data base of samples and incrementally design practical pattern recognizers, particularly for diagnostic applications. In this system, several well-known methods have been implemented, such as: Bayes' rule with independence and with 1st order dependence, and the K-nearest neighbor method. Adjustments can be made to the methods and the data base such that: only a subset of the features may be considered, decision boundaries varied, and misclassified patterns displayed. Frequencies and probability estimates for combinations of patterns of features are generated from the data base. In some cases, this leads to an effective alternative to the pattern recognition methods cited above. With a sufficiently large data base and a relatively small subset of features, complete dependence among features can sometimes be extracted. Probability estimates can be generated for combinations of patterns which cover all mutually exclusive possibilities. The design of a classifier is described which evaluates the prognosis of patients with bronchial asthma who are being considered for immunotherapy.",
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year = "1978",
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language = "English (US)",
pages = "58--62",
note = "Proc Int Conf Cybern Soc Tokyo, Jpn, Nov 3-5 ; Conference date: 07-11-1978 Through 07-11-1978",

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Weiss, SM, Kern, KB, Kulikowski, C & Pincus, W 1978, 'INTERACTIVE SYSTEM FOR THE DESIGN OF CLASSIFIERS IN DIAGNOSTIC APPLICATIONS.' Paper presented at Proc Int Conf Cybern Soc Tokyo, Jpn, Nov 3-5, Kyoto, Jpn, 11/7/78 - 11/7/78, pp. 58-62.

INTERACTIVE SYSTEM FOR THE DESIGN OF CLASSIFIERS IN DIAGNOSTIC APPLICATIONS. / Weiss, Sholom M.; Kern, Kevin B.; Kulikowski, Casimir; Pincus, William.

1978. 58-62 Paper presented at Proc Int Conf Cybern Soc Tokyo, Jpn, Nov 3-5, Kyoto, Jpn, .

Research output: Contribution to conferencePaper

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N2 - A computer system has been developed for the interactive design of pattern classifiers. The purpose of this system is to allow the researcher to interact with a data base of samples and incrementally design practical pattern recognizers, particularly for diagnostic applications. In this system, several well-known methods have been implemented, such as: Bayes' rule with independence and with 1st order dependence, and the K-nearest neighbor method. Adjustments can be made to the methods and the data base such that: only a subset of the features may be considered, decision boundaries varied, and misclassified patterns displayed. Frequencies and probability estimates for combinations of patterns of features are generated from the data base. In some cases, this leads to an effective alternative to the pattern recognition methods cited above. With a sufficiently large data base and a relatively small subset of features, complete dependence among features can sometimes be extracted. Probability estimates can be generated for combinations of patterns which cover all mutually exclusive possibilities. The design of a classifier is described which evaluates the prognosis of patients with bronchial asthma who are being considered for immunotherapy.

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Weiss SM, Kern KB, Kulikowski C, Pincus W. INTERACTIVE SYSTEM FOR THE DESIGN OF CLASSIFIERS IN DIAGNOSTIC APPLICATIONS.. 1978. Paper presented at Proc Int Conf Cybern Soc Tokyo, Jpn, Nov 3-5, Kyoto, Jpn, .