Machine Learning and Data Mining

"The field of machine learning was conceived with the bold objective to develop computational methods that would implement various forms of learning, in particular mechanisms capable of inducing knowledge from examples or data."

"Most methods for learning rules or decision trees from examples assume that the attributes used for describing examples are sufficiently relevant to the learning problem at hand. This assumption does not always hold in practice."

"Inductive Logic Programming (ILP) is a combination of inductive machine learning and logic programming."

"The "optimal" mesh model is the coarsest one that still ensures a satisfactory accuracy of the results."

"Inductive learning creates a general description of past examples, and then applies this description to new data."

"The key to building an effective planner is a learning issue: how to assimilate previously experienced assembly episodes, and how to bring them to bear in solving a new assembly problem."

"The problem for an association-discovery tool is to help a user identify the interesting results out of all those it generates."

"Learning capabilities can make vision systems more easily adaptable to different vision problems, and more flexible and robust in handling variable perceptual conditions."

"Computer viruses are self-replicating software entities that attach themselves parasitically to existing programs."

"Economic requirements go hand-in-hand with the need for assistance to human operators in order to perform reliably, effectively and safely in many different and sometimes unexpected circumstances."