Cubic generation conjecture for binary naive Bayes models

Let GG be a naive Bayes model with r=2r=2 classes, and let (pi1i2in)(p_{i_1 i_2 \cdots i_n}) be its nn-dimensional table. A flattening is any two-dimensional table obtained by partitioning the indices of this tensor into two groups; write QGQ_G for the prime ideal of the model.

Cubic generation conjecture. The prime ideal QGQ_G is generated by the 3×33\times 3-subdeterminants of any two-dimensional table obtained by flattening the nn-dimensional table (pi1i2in)(p_{i_1 i_2 \cdots i_n}).

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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