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Learning Optimized Or's of And's
Tong Wang, Cynthia Rudin
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 =…
Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model
Benjamin Letham, Cynthia Rudin, Tyler H. McCormick +1
We aim to produce predictive models that are not only accurate, but are also interpretable to human experts. Our models are decision lists, which consist of a series of if...then..…
Prediction uncertainty and optimal experimental design for learning dynamical systems
Benjamin Letham, Portia A. Letham, Cynthia Rudin +1
Dynamical systems are frequently used to model biological systems. When these models are fit to data it is necessary to ascertain the uncertainty in the model fit. Here we present…
Sparse Density Trees and Lists: An Interpretable Alternative to High-Dimensional Histograms
Siong Thye Goh, Lesia Semenova, Cynthia Rudin
We present sparse tree-based and list-based density estimation methods for binary/categorical data. Our density estimation models are higher dimensional analogies to variable bin w…
Causal Falling Rule Lists
Fulton Wang, Cynthia Rudin
A causal falling rule list (CFRL) is a sequence of if-then rules that specifies heterogeneous treatment effects, where (i) the order of rules determines the treatment effect subgro…
CRAFT: ClusteR-specific Assorted Feature selecTion
Vikas K. Garg, Cynthia Rudin, Tommi Jaakkola
We present a framework for clustering with cluster-specific feature selection. The framework, CRAFT, is derived from asymptotic log posterior formulations of nonparametric MAP-base…