implementation detail · filed under data curation
Prior-constrained Dirichlet mixture exploration
Samples candidate mixtures from a Dirichlet distribution centered on a prior and constrains their distance from it.
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One count per evidence span, weakest treatment to strongest.
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Evidence
1 span quoted from the sources, strongest treatment first.
Candidate mixtures are sampled as: x ∼ Dirichlet(αx₀) subject to additional constraints: ‖x − x₀‖₁ < ε
useddata curationin Laguna XS.2Poolside
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Other methods under data curation :: data mixture & curriculum.
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