Report for Contract W911NF-09-1-0205 (University of Wisconsin - Madison)

Abstract

Classification and regression tree methodology is an important and essential tool in statistics and machine learning. This research accomplished several improvements and advancements in the area and implemented them in the GUIDE computer software. The major contributions are (i) a new technique to deal with missing data values that allows all the information, including whether or not an observation is missing, to be used for tree construction and prediction, (ii) a new method of scoring the importance of variables that can be used to objectively reduce the number of variables for prediction modeling, (iii) a new approach to building regression models for data with multidimensional or longitudinal response variables that does not require any model assumptions, and (iv) several new techniques for identifying subgroups of the data for enhanced differential treatment effects.

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Document Details

Document Type
Technical Report
Publication Date
Jan 18, 2014
Accession Number
ADA606605

Entities

People

  • Wei-yin Loh

Organizations

  • University of Wisconsin–Madison

Tags

Communities of Interest

  • Human Systems

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  • Abstracts
  • Algorithms
  • Civil Engineering
  • Computer Programs
  • Computers
  • Data Mining
  • Data Sets
  • Department Of Defense
  • Education
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  • Machine Learning
  • Mathematics
  • Sea Surface Temperature
  • Statistics
  • Students
  • Surface Temperature

Readers

  • Computer Science.
  • Oncology and Biomarker-Based Cancer Detection.
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference