Random Forests and Decision Trees: Machine Learning, Empirical Statistics, and the Challenge of Interpretability

Update: 2016-11-19

Description

Matthew Jones from Columbia University delivers a talk titled “Random Forests and Decision Trees: Machine Learning, Empirical Statistics, and the Challenge of Interpretability.” This talk was included in the session titled “Methods and Ambiguities in the Contemporary Age.”

Part of “Histories of Data and the Database,” a conference held at The Huntington Nov. 18–19, 2016.

Comments

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Random Forests and Decision Trees: Machine Learning, Empirical Statistics, and the Challenge of Interpretability

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Random Forests and Decision Trees: Machine Learning, Empirical Statistics, and the Challenge of Interpretability

The Huntington

Random Forests and Decision Trees: Machine Learning, Empirical Statistics, and the Challenge of Interpretability