R and Data Mining: Examples and Case StudiesR and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more.Data mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation.With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, R and Data Mining is a valuable, practical guide to a powerful method of analysis.
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Contents
| 1 | |
| 5 | |
| 11 | |
Decision Trees and Random Forest | 27 |
Regression | 41 |
Clustering | 51 |
Outlier Detection | 63 |
Time Series Analysis and Mining | 75 |
Analysis and Forecasting of House Price Indices | 137 |
Customer Response Prediction and Profit Optimization | 151 |
Predictive Modeling of Big Data with Limited Memory | 181 |
Online Resources | 213 |
R Reference Card for Data Mining | 221 |
Bibliography | 225 |
| 229 | |
| 231 | |
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2013 Yanchang Zhao Age=Adult algorithm barplot big data boxplot CARDPM12 categorical variables chapter chart Class=2nd Class=3rd Class=Crew classification components CSV file ctree data frame Data Mining database dataset decision tree density-based Discrete Wavelet Transform distribution donation amount Dynamic Time Warping Elsevier Inc examples Factor Figure foreach forecasting function GENDER graph hierarchical clustering hipcirc Increase Rate itemsets k-means clustering k-medoids labels LASTDATE levels linear regression MaxSurrogate MINRAMNT MinSplit missing values myCtree Node NULL number of clusters outlier detection package party package version Parallel Computing parallel coordinates parameters PEPSTRFL Percentage Percentile predict Published by Elsevier random forest Reference Card result RFA_2A rpart scatter plot score data Series Analysis setosa versicolor virginica Sex=Female Sex=Male silhouette social network analysis statistic stats Survived=Yes TARGET_D term-document matrix text mining topic models training data tutorial tweets Twitter vertices waistcirc wavelet words x$splitpoint