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Mastering Predictive Analytics with R

You're reading from   Mastering Predictive Analytics with R Master the craft of predictive modeling by developing strategy, intuition, and a solid foundation in essential concepts

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Product type Paperback
Published in Jun 2015
Publisher
ISBN-13 9781783982806
Length 414 pages
Edition 1st Edition
Languages
Tools
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Toc

Table of Contents (13) Chapters Close

Preface 1. Gearing Up for Predictive Modeling 2. Linear Regression FREE CHAPTER 3. Logistic Regression 4. Neural Networks 5. Support Vector Machines 6. Tree-based Methods 7. Ensemble Methods 8. Probabilistic Graphical Models 9. Time Series Analysis 10. Topic Modeling 11. Recommendation Systems Index

Index

A

  • ACF function
    • about / Time series summary functions
  • activators
    • about / The biological neuron
  • acyclic graph
    • about / A little graph theory
  • AdaBoost / AdaBoost
  • AdaBoost, for binary classification
    • inputs / AdaBoost
    • output / AdaBoost
    • observations / AdaBoost
  • adaptive boosting
    • about / AdaBoost
  • additive smoothing
    • about / Predicting the sentiment of movie reviews
  • Akaike Information Criterion (AIC)
    • about / Comparing different regression models
  • algorithms
    • building, to train decision trees / Algorithms for training decision trees
  • analysis of variance
    • about / Significance tests for linear regression
  • ARCH models / Autoregressive conditional heteroscedasticity models
  • ARIMA models / Autoregressive integrated moving average models
  • ARMA model / Autoregressive moving average models
  • artificial neural networks (ANNs)
    • about / The biological neuron
  • artificial neuron
    • about / The...
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