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Mastering Machine Learning with R

You're reading from   Mastering Machine Learning with R Master machine learning techniques with R to deliver insights for complex projects

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Product type Paperback
Published in Oct 2015
Publisher
ISBN-13 9781783984527
Length 400 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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Cory Lesmeister Cory Lesmeister
Author Profile Icon Cory Lesmeister
Cory Lesmeister
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Toc

Table of Contents (15) Chapters Close

Preface 1. A Process for Success FREE CHAPTER 2. Linear Regression – The Blocking and Tackling of Machine Learning 3. Logistic Regression and Discriminant Analysis 4. Advanced Feature Selection in Linear Models 5. More Classification Techniques – K-Nearest Neighbors and Support Vector Machines 6. Classification and Regression Trees 7. Neural Networks 8. Cluster Analysis 9. Principal Components Analysis 10. Market Basket Analysis and Recommendation Engines 11. Time Series and Causality 12. Text Mining A. R Fundamentals Index

Index

A

  • Aikake's Information Criterion (AIC) / Modeling and evaluation
    • about / Granger causality
  • algorithm flowchart
    • about / Algorithm flowchart
  • American Diabetes Association (ADA)
    • URL / Business understanding
  • apriori algorithms
    • about / An overview of a market basket analysis
  • Area Under the Curve (AUC)
    • about / Model selection
  • Artificial Neural Networks (ANNs)
    • about / Neural network
    • reference link / Neural network
  • arules* Mining Association Rules and Frequent Itemsets
    • about / An overview of a market basket analysis
  • Augmented Dickey-Fuller (ADF) test
    • about / Data understanding and preparation
  • Autocorrelation Function (ACF)
    • about / Univariate time series analysis
  • Autoregressive Integrated Moving Average (ARIMA) models
    • about / Univariate time series analysis

B

  • Back Propagation
    • about / Neural network
  • backward stepwise regression / Modeling and evaluation
  • bagging...
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