Because of its promise to support human programmers in developing correct and efficient program code and in reasoning about programs, automatic program synthesis has attracted the attention of researchers and professionals since the 1970s.
This book focusses on inductive program synthesis, and especially on the induction of recursive functions; it is organized into three parts on planning, inductive program synthesis, and analogical problem solving and learning. Besides methodological issues in inductive program synthesis, emphasis is placed on its applications to control rule...
Because of its promise to support human programmers in developing correct and efficient program code and in reasoning about programs, automatic pro...
This work discusses the theoretical abilities of three commonly used classifier learning methods and optimization techniques to cope with characteristics of real-world classification problems, more specifically varying misclassification costs, imbalanced data sets and varying degrees of hardness of class boundaries. From these discussions a universally applicable optimization framework is derived that successfully corrects the error-based inductive bias of classifier learning methods on image data within the domain of medical diagnosis. The framework was designed considering several points...
This work discusses the theoretical abilities of three commonly used classifier learning methods and optimization techniques to cope with characterist...
