Random errors and insufficiencies in databases limit the performance of any classifier trained from and applied to the database. In this paper we propose a method to estimate the ...
Corinna Cortes, Lawrence D. Jackel, Wan-Ping Chian...
There has been much recent interest in on-line data mining. Existing mining algorithms designed for stored data are either not applicable or not effective on data streams, where r...
Association Rules Mining (ARM) algorithms are designed to find sets of frequently occurring items in large databases. ARM applications have found their way into a variety of field...
Database integration of data mining has gained popularity and its significance is well recognized. However, the performance of SQL based data mining is known to fall behind specia...
To address the of mining a huge volume of geographically distributed databases, we propose two approaches. The first one is to download only a sample of each database. The second ...