Machine learning with R : learn how to use R to apply powerful machine learning methods and gain an insight into real-world applications /
375 p. ; ill. Includes index. Content notes : Chapter 1: Introducing machine learning--
Chapter 2: Managing and understanding data--
Chapter 3: Lazy learning-classification using nearest neighbors--
Chapter 4: Probabilistic learning-classification using naive Bayes--
Chapter 5: Divide and conquer-classification using decision trees and rules--
Chapter 6: Forecasting numeric data-regression methods--
Chapter 7: Black box methods-neural networks and support vector machines--
Chapter 8: Finding patterns-market basket analysis using association rules--
Chapter 9: Finding groups of data-clustering with k-means--
Chapter 10: Evaluating model performance--
Chapter 11: Improving model performance--
Chapter 12: Specialized machine learning topics--
Summary--
Index. R (Computer program language).
