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A general approach for predicting the behavior of the Supreme Court of the United States
Building on developments in machine learning and prior work in the science of judicial prediction, we construct a model designed to predict the behavior of the Supreme Court of the United States in a generalized, out-of-sample context. To do so, we develop a time-evolving random forest classifier th...
Autores principales: | Katz, Daniel Martin, Bommarito, Michael J., Blackman, Josh |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5389610/ https://www.ncbi.nlm.nih.gov/pubmed/28403140 http://dx.doi.org/10.1371/journal.pone.0174698 |
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