Random Forests for the Social Sciences Zachary Jones and Fridolin Linder∗ Abstract Machine learning techniques gain in popularity in many disciplines and increased computational power allows for easy implementation of - Power gain - Document - PDFSEARCH.IO

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	Random Forests for the Social Sciences Zachary Jones and Fridolin Linder∗ Abstract Machine learning techniques gain in popularity in many disciplines and increased computational power allows for easy implementation of Add to Reading List Document Date: 2015-04-12 13:23:45 Open Document File Size: 2,28 MB Share Result on Facebook / Facility Pennsylvania State University / / IndustryTerm heuristic algorithms / stochastic search algorithm / partial dependence algorithm / recursive partitioning algorithm / recursive partitioning algorithms / / Organization Pennsylvania State University / United States Department of State / / Person Beck / Zachary M. Jones / / Position King / analyst / Marshall / / ProgrammingLanguage R / / Technology 2 This algorithm / CART algorithm / partitioning algorithm / recursive partitioning algorithm / Machine learning / recursive partitioning algorithms / partial dependence algorithm / stochastic search algorithm / data modeling / Instead heuristic algorithms / / SocialTag Decision tree learning Resampling Least squares Ordinary least squares Variance Degrees of freedom Random variable Bootstrapping Errors and residuals in statistics Statistics

Random Forests for the Social Sciences Zachary Jones and Fridolin Linder∗ Abstract Machine learning techniques gain in popularity in many disciplines and increased computational power allows for easy implementation of Add to Reading List