Selecting Models from Data: Artificial Intelligence and Statistics IV: 89 (Lecture Notes in Statistics) - Tapa blanda

This volume is a selection of papers presented at the Fourth International Workshop on Artificial Intelligence and Statistics held in January 1993. These biennial workshops have succeeded in bringing together researchers from Artificial Intelligence and from Statistics to discuss problems of mutual interest. The exchange has broadened research in both fields and has strongly encour­ aged interdisciplinary work. The theme ofthe 1993 AI and Statistics workshop was: "Selecting Models from Data". The papers in this volume attest to the diversity of approaches to model selection and to the ubiquity of the problem. Both statistics and artificial intelligence have independently developed approaches to model selection and the corresponding algorithms to implement them. But as these papers make clear, there is a high degree of overlap between the different approaches. In particular, there is agreement that the fundamental problem is the avoidence of "overfitting"-Le., where a model fits the given data very closely, but is a poor predictor for new data; in other words, the model has partly fitted the "noise" in the original data.

This volume presents a selection of papers from the Fourth International Workshop on Artificial Intelligence and Statistics. This biennial workshop brings together researchers from both fields to discuss problems of mutual interest and to compare approaches to their solution. The fourth workshop focused on the topic of selecting models from data. As the papers in this volume attest, the empirical approaches from the two separate fields have much in common yet still depart enough from one another to stimulate active interdisciplinary work. The papers cover a wide spectrum of problems in empirical modelling including model selection in general, graphical models, causal models, regression and other statistical models, and general algorithms and software tools. This timely volume will benefit all researchers with an active interest in model selection, empirical model building, or more generally the interaction between Statistics and Artificial Intelligence.