<p><a href="https://bbs.pinggu.org/thread-1409460-1-1.html"><font color="#000000">data mining</font></a><font size="3">[usemoney=10]&nbsp;</font><font size="3">[usemoney]&nbsp;</font><br></p><p></p><p>Contents<br>Preface iii<br>1 Introduction 1<br>1.1 How to read this book? . . . . . . . . . . . . . . . . . . . . . . . 2<br>1.2 A short introduction to R . . . . . . . . . . . . . . . . . . . . . . 3<br>1.2.1 Starting with R . . . . . . . . . . . . . . . . . . . . . . . . 3<br>1.2.2 R objects . . . . . . . . . . . . . . . . . . . . . . . . . . . 5<br>1.2.3 Vectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6<br>1.2.4 Vectorization . . . . . . . . . . . . . . . . . . . . . . . . . 8<br>1.2.5 Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9<br>1.2.6 Generating sequences . . . . . . . . . . . . . . . . . . . . 11<br>1.2.7 Indexing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12<br>1.2.8 Matrices and arrays . . . . . . . . . . . . . . . . . . . . . 14<br>1.2.9 Lists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17<br>1.2.10 Data frames . . . . . . . . . . . . . . . . . . . . . . . . . . 20<br>1.2.11 Some useful functions . . . . . . . . . . . . . . . . . . . . 23<br>1.2.12 Creating new functions . . . . . . . . . . . . . . . . . . . 25<br>1.2.13 Managing your sessions . . . . . . . . . . . . . . . . . . . 28<br>1.3 A short introduction to MySQL . . . . . . . . . . . . . . . . . . . 29<br>2 Predicting Algae Blooms 33<br>2.1 Problem description and objectives . . . . . . . . . . . . . . . . . 33<br>2.2 Data Description . . . . . . . . . . . . . . . . . . . . . . . . . . . 34<br>2.3 Loading the data into R . . . . . . . . . . . . . . . . . . . . . . . 34<br>2.4 Data Visualization and Summarization . . . . . . . . . . . . . . . 35<br>2.5 Unknown values . . . . . . . . . . . . . . . . . . . . . . . . . . . 42<br>2.5.1 Removing the observations with unknown values . . . . . 43<br>2.5.2 Filling in the unknowns with the most frequent values . . 44<br>2.5.3 Filling in the unknown values by exploring correlations . 45<br>2.5.4 Filling in the unknown values by exploring similarities<br>between cases . . . . . . . . . . . . . . . . . . . . . . . . . 48<br>2.6 Obtaining prediction models . . . . . . . . . . . . . . . . . . . . . 52<br>2.6.1 Multiple linear regression . . . . . . . . . . . . . . . . . . 52<br>2.6.2 Regression trees . . . . . . . . . . . . . . . . . . . . . . . 58<br>2.7 Model evaluation and selection . . . . . . . . . . . . . . . . . . . 64<br>2.8 Predictions for the 7 algae . . . . . . . . . . . . . . . . . . . . . . 70<br>2.8.1 Preparing the test data . . . . . . . . . . . . . . . . . . . 71<br>2.8.2 Comparing the alternative models . . . . . . . . . . . . . 71<br>2.8.3 Obtaining the prediction for the test samples . . . . . . . 74<br>2.9 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77<br>3 Predicting Stock Market Returns 79<br>3.1 Problem description and objectives . . . . . . . . . . . . . . . . . 79<br>3.2 The available data . . . . . . . . . . . . . . . . . . . . . . . . . . 80<br>3.2.1 Reading the data from the CSV file . . . . . . . . . . . . 81<br>3.2.2 Reading the data from a MySQL database . . . . . . . . . 82<br>3.2.3 Getting the data from the Web . . . . . . . . . . . . . . . 85<br>3.3 Time series predictions . . . . . . . . . . . . . . . . . . . . . . . . 87<br>3.3.1 Obtaining time series prediction models . . . . . . . . . . 90<br>3.3.2 Evaluating time series models . . . . . . . . . . . . . . . . 96<br>3.3.3 Model selection . . . . . . . . . . . . . . . . . . . . . . . . 100<br>3.4 From predictions into trading actions . . . . . . . . . . . . . . . . 103<br>3.4.1 Evaluating trading signals . . . . . . . . . . . . . . . . . . 104<br>3.4.2 A simulated trader . . . . . . . . . . . . . . . . . . . . . . 106<br>3.5 Going back to data selection . . . . . . . . . . . . . . . . . . . . . 110<br>3.5.1 Enriching the set of predictor variables . . . . . . . . . . . 110<br>Bibliography 119<br>(DRAFT - May 22, 2003)</p>