𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Learning from imperfect data

✍ Scribed by Pitoyo Hartono; Shuji Hashimoto


Publisher
Elsevier Science
Year
2007
Tongue
English
Weight
583 KB
Volume
7
Category
Article
ISSN
1568-4946

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


Learning concepts from data
✍ Donald Michie πŸ“‚ Article πŸ“… 1998 πŸ› Elsevier Science 🌐 English βš– 444 KB

Current data-mining practice employs relatively low-level machine learning algorithms-statistical, neural-net, genetic, decision-tree, etc.-to trawl large data-sets for new classifiers. Usefulness of classifiers is then assessed according to accuracy in classifying new data, e.g. for stockmarket pre

Learning indistinguishability from data
✍ F. HΓΆppner; F. Klawonn; P. Eklund πŸ“‚ Article πŸ“… 2002 πŸ› Springer 🌐 English βš– 294 KB
Incremental Learning from Positive Data
✍ Steffen Lange; Thomas Zeugmann πŸ“‚ Article πŸ“… 1996 πŸ› Elsevier Science 🌐 English βš– 835 KB

The present paper deals with a systematic study of incremental learning algorithms. The general scenario is as follows. Let c be any concept; then every infinite sequence of elements exhausting c is called positive presentation of c. An algorithmic learner successively takes as input one element of

Learning Fuzzy Rules from Data
✍ G.D. Finn πŸ“‚ Article πŸ“… 1999 πŸ› Springer-Verlag 🌐 English βš– 135 KB
Learning qualitative models from numeric
✍ Jure Ε½abkar; Martin MoΕΎina; Ivan Bratko; Janez DemΕ‘ar πŸ“‚ Article πŸ“… 2011 πŸ› Elsevier Science 🌐 English βš– 462 KB
Imperfect information, Bayesian learning
✍ Graziella Bertocchi; Yong Wang πŸ“‚ Article πŸ“… 1996 πŸ› Springer 🌐 English βš– 978 KB

This paper examines the consequences of informational imperfections for economic growth in an overlapping generations model in which agents learn the technological parameters in a Bayesian fashion. Under mild sufficient conditions, beliefs converge to the true value of the technological parameters.