Predicting survival in malignant skin melanoma using Bayesian networks automatically induced by genetic algorithms. An empirical comparison between different approaches

@article{Sierra1998PredictingSI,
  title={Predicting survival in malignant skin melanoma using Bayesian networks automatically induced by genetic algorithms. An empirical comparison between different approaches},
  author={Basilio Sierra and Pedro Larra{\~n}aga},
  journal={Artificial intelligence in medicine},
  year={1998},
  volume={14 1-2},
  pages={215-30}
}
In this work we introduce a methodology based on genetic algorithms for the automatic induction of Bayesian networks from a file containing cases and variables related to the problem. The structure is learned by applying three different methods: The Cooper and Herskovits metric for a general Bayesian network, the Markov blanket approach and the relaxed Markov blanket method. The methodologies are applied to the problem of predicting survival of people after 1, 3 and 5 years of being diagnosed… CONTINUE READING

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