Machine Learning with R
Written as a tutorial to explore and understand the power of R for machine learning. This practical guide covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the r...
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| Hlavní autor: | |
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| Médium: | E-kniha |
| Jazyk: | angličtina |
| Vydáno: |
Packt Publishing
2013
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| Témata: | |
| ISBN: | 9781782162148, 1782162143 |
| On-line přístup: | Získat plný text |
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Obsah:
- Title Page Preface Table of Contents 1. Introducing Machine Learning 2. Managing and Understanding Data 3. Lazy Learning - Classification Using Nearest Neighbors 4. Probabilistic Learning - Classification Using Naive Bayes 5. Divide and Conquer - Classification Using Decision Trees and Rules 6. Forecasting Numeric Data - Regression Methods 7. Black Box Methods - Neural Networks and Support Vector Machines 8. Finding Patterns - Market Basket Analysis Using Association Rules 9. Finding Groups of Data - Clustering with k-Means 10. Evaluating Model Performance 11. Improving Model Performance 12. Specialized Machine Learning Topics Index