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Falling rule lists are classification models consisting of an ordered list of if-then rules, where (i) the order of rules determines which example should be classified by each rule, and (ii) the estimated probability of success decreases monotonically down the list.
Prognostic signs and the role of operative management in acute pancreatitis
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APACHE-acute physiology and chronic health evaluation: a physiologically based classification system
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Breiman, Leo, Friedman, Jerome H., Olshen, Richard A., & Stone, Charles J. 1984 · 1984
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Knaus, William A, Draper, Elizabeth A, Wagner, Douglas P, & Zimmerman, Jack E. 1985 · 1985
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Quinlan, J. Ross. 1986 · 1986
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Learning decision lists
Rivest, Ronald L. 1987 · 1987
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Very simple classification rules perform well on most commonly used datasets
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Monotonicity maintenance in information-theoretic machine learning algorithms
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Chipman, Hugh A, George, Edward I, & McCulloch, Robert E. 1998 · 1998
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Antman, Elliott M, Cohen, Marc, Bernink, Peter JLM, McCabe, Carolyn H, Horacek, Thomas, Papuchis, Gary, Mautner, Branco, Corbalan, Ramon, Radley, David, & Braunwald, Eugene. 2000 · 2000
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Pazzani, Michael J. 2000 · 2000
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Gage, Brian F, Waterman, Amy D, Shannon, William, Boechler, Michael, Rich, Michael W, & Radford, Martha J. 2001 · 2001
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Acceptance of rules generated by machine learning among medical experts
Pazzani, MJ, Mani, S, & Shankle, WR. 2001 · 2001
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Pruning for monotone classification trees
Feelders, Ad, & Pardoel, Martijn. 2003 · 2003
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Dunson, David B. 2004 · 2004
Building acceptable classification models
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User-oriented Assessment of Classification Model Understandability
Allahyari, Hiva, & Lavesson, Niklas. 2011 · 2011
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An empirical evaluation of the comprehensibility of decision table, tree and rule based predictive models
Huysmans, Johan, Dejaeger, Karel, Mues, Christophe, Vanthienen, Jan, & Baesens, Bart. 2011 · 2011
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Performance of classification models from a user perspective
Martens, David, Vanthienen, Jan, Verbeke, Wouter, & Baesens, Bart. 2011 · 2011
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Partially collapsed Gibbs sampling and path-adaptive Metropolis-Hastings in high-energy astrophysics
van Dyk, David A, & Park, Taeyoung. 2011 · 2011
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Building comprehensible customer churn prediction models with advanced rule induction techniques
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Thabtah, Fadi. 2007 · 2007
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Verbeke, Wouter, Martens, David, Mues, Christophe, & Baesens, Bart. 2011 · 2011
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Ridgeway, Greg. 2013 · 2013
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Work In Progress
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Comprehensible classification models: a position paper
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Bayesian OrÕs of AndÕs for Interpretable Classification with Application to Context Aware Recommender Systems
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TIMI risk score for ST-elevation myocardial infarction: a convenient, bedside, clinical score for risk assessment at presentation an intravenous nPA for treatment of infarcting myocardium early II trial substudy
Morrow, David A, Antman, Elliott M, Charlesworth, Andrew, Cairns, Richard, Murphy, Sabina A, de Lemos, James A, Giugliano, Robert P, McCabe, Carolyn H, & Braunwald, Eugene. 2000 · 2037
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