Learning Optimized Or's of And's

Understand

Or's of And's (OA) models are comprised of a small number of disjunctions of conjunctions, also called disjunctive normal form.

• An example of an OA model is as follows: If ($x_1 = $ `blue' AND $x_2=$ `middle') OR ($x_1 = $ `yellow'), then predict $Y=1$, else predict $Y=0$.
• Or's of And's models have the advantage of being interpretable to human experts, since they are a set of conditions that concisely capture the characteristics of a specific subset of data.
• We present two optimization-based machine learning frameworks for constructing OA models, Optimized OA (OOA) and its faster version, Optimized OA with Approximations (OOAx).