Book Contents

• Cover
• Chapter 1: Introduction
• Chapter 2: Predicting Algae Blooms
• Chapter 3: Predicting Stock Market Returns
• Chapter 4: Detecting Fraudulent Transactions
• Chapter 5: Classifying Microarray Samples
• Bibliography
• Index
• Index of Data Mining Topics
• Index of R Functions

Chapter 5 - Classifying Microarray Samples

• 5.1 Problem Description and Objectives
• 5.1.1 Short Background on Microarray Experiments
• 5.1.2 The ALL data set
• 5.2 The Available Data
• 5.2.1 Exploring the data set
• 5.3 Gene (Feature) Selection
• 5.3.1 Simple filters based on distribution properties
• 5.3.2 ANOVA filters
• 5.3.3 Filtering using Random Forests
• 5.3.4 Filtering using feature clustering ensembles
• 5.4 Predicting Cytogenetic Abnormalities
• 5.4.1 Defining the prediction task
• 5.4.2 The evaluation metric
• 5.4.3 The experimental procedure
• 5.4.4 The modeling techniques
• 5.4.5 Comparing the models
• 5.5 Summary