WIT Press


Learning From Data: Building, Evaluating And Understanding Models

Price

Free (open access)

Paper DOI

10.2495/DATA980011

Volume

22

Pages

2

Published

1998

Size

233 kb

Author(s)

Andreas S. Weigend

Abstract

of the Invited Technical Conference Analyzing tick-by-tick market data in real time, uncovering trading styles and understanding their profit and risk characteristics, managing portfolios of thousands of securities, and flagging potential fraud in millions of daily transactions are some of the challenges now sweeping the financial industries. Knowledge discovery and data mining approaches address these challenges and try to extract previously unknown, valid and comprehensible knowledge from large data sets. These approaches have emerged from several historically disjoint communities that include artificial intelligence, neural networks, evolutionary programming, reinforcement learning, signal processing, decision science, statistics, econometrics, probabilistic modeling and computational learning.

Keywords