Cubic generation conjecture for binary naive Bayes models
Cubic generation conjecture for binary naive Bayes models
Let be a naive Bayes model with classes, and let be its -dimensional table. A flattening is any two-dimensional table obtained by partitioning the indices of this tensor into two groups; write for the prime ideal of the model.
Cubic generation conjecture. The prime ideal is generated by the -subdeterminants of any two-dimensional table obtained by flattening the -dimensional table .
The conjecture is motivated by computations showing cubic generators in the displayed examples. It asserts a uniform determinantal generating set for all binary naive Bayes models, but the supplied text gives no resolution or proof beyond those computations.
Sources & referencesView supporting material
Primary source
Luis David Garcia, Michael Stillman and Bernd Sturmfels, “Algebraic Geometry of Bayesian Networks”, arXiv:math/0301255 (2003).
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