To Select or To Weigh: A Comparative Study of Linear Combination Schemes for SuperParent-One-Dependence Estimators

@article{Yang2007ToSO,
  title={To Select or To Weigh: A Comparative Study of Linear Combination Schemes for SuperParent-One-Dependence Estimators},
  author={Ying Yang and Geoffrey I. Webb and Jes{\'u}s Cerquides and Kevin B. Korb and Janice R. Boughton and Kai Ming Ting},
  journal={IEEE Transactions on Knowledge and Data Engineering},
  year={2007},
  volume={19},
  pages={1652-1665}
}
We conduct a large-scale comparative study on linearly combining superparent-one-dependence estimators (SPODEs), a popular family of seminaive Bayesian classifiers. Altogether, 16 model selection and weighing schemes, 58 benchmark data sets, and various statistical tests are employed. This paper's main contributions are threefold. First, it formally presents each scheme's definition, rationale, and time complexity and hence can serve as a comprehensive reference for researchers interested in… CONTINUE READING
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