Decision Forests: A Unified Framework for Classification, Regression, Density Estimation, Manifold Learning and Semi-Supervised Learning

In recent years decision forests have established themselves as one of the most promising techniques in machine learning, computer vision and medical image analysis. This book is directed at engineers and PhD students who wish to learn the basics of decision forests as well as more senior researchers who wish to push the state of the art in automated image understanding. The authors presents a unified, efficient model of random decision forests which can be used in a number of applications such as scene recognition from photographs, object recognition in images, automatic diagnosis from radiological scans and document analysis. Such applications have traditionally been addressed by different, supervised or…