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R Machine Learning By Example

You're reading from   R Machine Learning By Example Understand the fundamentals of machine learning with R and build your own dynamic algorithms to tackle complicated real-world problems successfully

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Product type Paperback
Published in Mar 2016
Publisher
ISBN-13 9781784390846
Length 340 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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Raghav Bali Raghav Bali
Author Profile Icon Raghav Bali
Raghav Bali
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Toc

Table of Contents (10) Chapters Close

Preface 1. Getting Started with R and Machine Learning FREE CHAPTER 2. Let's Help Machines Learn 3. Predicting Customer Shopping Trends with Market Basket Analysis 4. Building a Product Recommendation System 5. Credit Risk Detection and Prediction – Descriptive Analytics 6. Credit Risk Detection and Prediction – Predictive Analytics 7. Social Media Analysis – Analyzing Twitter Data 8. Sentiment Analysis of Twitter Data Index

Index

A

  • active-user / Result interpretation
  • Adaptive Boosting (AdaBoost) / Boosting
  • algorithms
    • family / Families of algorithms
    • supervised learning algorithms / Supervised learning algorithms
    • linear regression / Linear regression
    • K-Nearest Neighbors (KNN) / K-Nearest Neighbors (KNN)
  • analytics
    • about / Types of analytics
    • descriptive / Types of analytics
    • diagnostic / Types of analytics
    • predictive / Types of analytics
    • prescriptive / Types of analytics
  • apply function / apply
  • Apriori algorithm / Apriori algorithm
  • Area under curve (AUC) / Evaluating predictive models
  • arrays and matrices
    • about / Arrays and matrices
    • creating / Creating arrays and matrices
  • Association for Computational Linguistics (ACL) / Feature extraction
  • association rule mining
    • about / Association rule mining
    • dependencies and data, loading / Loading dependencies and data
    • exploratory analysis / Exploratory analysis
    • shopping trends, detecting /...
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