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This work presents two complementary studies that propose heuristic methods to capture characteristics of data using the ensemble learning method of random forest. The first study is motivated by the

This work presents two complementary studies that propose heuristic methods to capture characteristics of data using the ensemble learning method of random forest. The first study is motivated by the problem in education of determining teacher effectiveness in student achievement. Value-added models (VAMs), constructed as linear mixed models, use students’ test scores as outcome variables and teachers’ contributions as random effects to ascribe changes in student performance to the teachers who have taught them.

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    Date Created
    • 2013
    Resource Type
  • Text
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    Note
    • Partial requirement for: Ph.D., Arizona State University, 2013
      Note type
      thesis
    • Includes bibliographical references (p. 150-153)
      Note type
      bibliography
    • Field of study: Statistics

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    by Arturo Valdivia

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