Author: Usama
“A Learning Approach to Object Recognition: Applications in Science Image Database Exploration and Analysis” U.M. Fayyad, P. Smyth, M.C. Burl, & P. Perona. A chapter in Early Visual Learning, S. Nayar and T. Poggio (Eds.), Oxford University Press (1998).
“Refining Initial Points for K-Means Clustering” Paul Bradley, Usama Fayyad. ICML 1998, Pro. of the 15th International Conference on Machine Learning, pp. 91-99, Morgan Kaufmann, Madison, Wisconson, July (1998).
A Tutorial on Support Vector Machines for Pattern Recognition
Abstract. The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines
Invited Speaker – Machines that Learn Workshop – Snowbird 1998, Snowbird, UT, April 1998.
Mining Your Own Business
Vendors seek to ease deployment as more companies look to data mining to turn data into profits. With transaction volumes rising and databases getting bigger,
Fayyad, U. “Taming the Giants and the Monsters: Mining Large Databases for Nuggets of Knowledge”, Database Programming and Design
[Phoenix, AZ, 3/4/97, 9:30PM, office of COO, TLI Communications Corp] “But how do we find those guys?” asked Underwood, “there’s some 10 billion records
“Mining Databases: Towards Algorithms for Knowledge Discovery” Usama Fayyad.. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering, Vol. 21, No. 1, pp. 39-48, March (1998).
1 Introduction Data Mining and Knowledge Discovery in Databases (KDD) are rapidly evolving areas of research that are at the intersection of several disciplines,