Pat Langley’s scientific contributions

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Publications (1)


Induction of Recursive Bayesian Classifiers.
  • Conference Paper

April 1993

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27 Reads

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306 Citations

Lecture Notes in Computer Science

Pat Langley

In this paper, we review the induction of simple Bayesian classifiers, note some of their drawbacks, and describe a recursive algorithm that constructs a hierarchy of probabilistic concept descriptions. We posit that this approach should outperform the simpler scheme in domains that involve disjunctive concepts, since they violate the independence assumption on which the latter relies. To test this hypothesis, we report experimental studies with both natural and artificial domains. The results are mixed, but they are encouraging enough to recommend closer examination of recursive Bayesian classifiers in future work.

Citations (1)


... The naive independence assumption can harm the performance when violated. In order to better deal with highly correlated variables, the selective naive Bayes approach [18] exploits a wrapper approach [16] to select the subset of variables which optimizes the classification accuracy. Another way to improve the learned classifiers is to train multiple models, in our case several selective naive Bayes classifiers with different subsets of variables, and combine them using model averaging (see for example [12]). ...

Reference:

Fractional Naive Bayes (FNB): non-convex optimization for a parsimonious weighted selective naive Bayes classifier
Induction of Recursive Bayesian Classifiers.
  • Citing Conference Paper
  • April 1993

Lecture Notes in Computer Science