Report on Preliminary Experiments with Data Grid Models in the Agnostic Learning vs. Prior Knowledge Challenge

@article{Boull2007ReportOP,
  title={Report on Preliminary Experiments with Data Grid Models in the Agnostic Learning vs. Prior Knowledge Challenge},
  author={Marc Boull{\'e}},
  journal={2007 International Joint Conference on Neural Networks},
  year={2007},
  pages={3092-3097}
}
This paper introduces a new method1 to automatically, rapidly and reliably evaluate the class conditional information of any subset of variables in supervised learning. It is based on a partitioning of each input variable, in intervals in the numerical case and in groups of values in the categorical case. The cross-product of the univariate partitions forms a multivariate partition of the input representation space into a set of cells. This multivariate partition, called data grid, allows to… CONTINUE READING
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