Decision forests for computer vision and medical image analysis

摘要

Decision trees have proven useful for classification and regression, as well as other types of discrimination problems. A collection of decision trees, varying in specific ways related to their training data and/or configuration, is referred to as a decision forest (or random forest). This book is a comprehensive presentation of the theory and use of decision forests in a wide range of applications, centered on computer vision and medical imaging. The book is strikingly well integrated. Early chapters provide an introduction to tree-based methods that is approachable by readers new to the field, followed by the application of these methods to the two common problems of classification and regression.