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1004 results in Computational statistics, machine learning and information science

Page 17 of 51

  • 10 - Information Theory and Decision Trees

  • from Part III - Classifiers and Tools
  • Jianxin Wu, Nanjing University, China
  • Book:
    Essentials of Pattern Recognition
    Published online:
    08 December 2020
    Print publication:
    19 November 2020, pp 219-242

  • Summary

    Information theory is developed in the communications community, but it turns out to be very useful for pattern recognition. In this chapter, we start with an example to develop the ideas of uncertainty and its measurement, i.e., entropy. A few core results in information theory are introduced: entropy, joint and conditional entropy, mutual information, and their relationships. We then move to differential entropy for continuous random variables and find distributions with maximum entropy under certain constraints, which are useful for pattern recognition. Finally, we introduce the applications of information theory in our context: maximum entropy learning, minimum cross entropy, feature selection, and decision trees (a widely used family of models for pattern recognition and machine learning).

Foundations of Probabilistic Programming
  • Edited by Gilles Barthe, Joost-Pieter Katoen, Alexandra Silva
  • Published online:
    18 November 2020
    Print publication:
    03 December 2020
  • What does a probabilistic program actually compute? How can one formally reason about such probabilistic programs? This valuable guide covers such elementary questions and more. It provides a state-of-the-art overview of the theoretical underpinnings of modern probabilistic programming and their applications in machine learning, security, and other domains, at a level suitable for graduate students and non-experts in the field. In addition, the book treats the connection between probabilistic programs and mathematical logic, security (what is the probability that software leaks confidential information?), and presents three programming languages for different applications: Excel tables, program testing, and approximate computing. This title is also available as Open Access on Cambridge Core.

Page 17 of 51