Luis Torgo is an associate professor in the Department of Computer Science at the University of Porto in Portugal. An active researcher in machine learning and data mining for more than 20 years, Dr. Torgo is also a researcher in the Laboratory of Artificial Intelligence and Data Analysis (LIAAD) of INESC Porto LA.

Introduction How to Read This Book A Short Introduction to R A Short Introduction to MySQL Predicting Algae Blooms Problem Description and Objectives Data Description Loading the Data into R Data Visualization and Summarization Unknown Values Obtaining Prediction Models Model Evaluation and Selection Predictions for the 7 Algae Predicting Stock Market Returns Problem Description and Objectives The Available Data Defining the Prediction Tasks The Prediction Models From Predictions into Actions Model Evaluation and Selection The Trading System Detecting Fraudulent Transactions Problem Description and Objectives The Available Data Defining the Data Mining Tasks Obtaining Outlier Rankings Classifying Microarray Samples Problem Description and Objectives The Available Data Gene (Feature) Selection Predicting Cytogenetic Abnormalities Bibliography Index Index of Data Mining Topics Index of R Functions

"This hands-on book uses practical examples to illustrate the power of R and data mining. Assuming no prior knowledge of R or data mining/statistical techniques, it covers a diverse set of problems that pose different challenges in terms of size, type of data, goals of analysis, and analytical tools. The main data mining processes and techniques are presented through detailed, real-world case studies. With these case studies, the author supplies all necessary steps, code, and data. Mirroring the do-it-yourself approach of the text, the supporting website provides data sets and R code"--