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AUSDM
2006
Springer
177views Data Mining» more  AUSDM 2006»
13 years 11 months ago
On The Optimal Working Set Size in Serial and Parallel Support Vector Machine Learning With The Decomposition Algorithm
The support vector machine (SVM) is a wellestablished and accurate supervised learning method for the classification of data in various application fields. The statistical learnin...
Tatjana Eitrich, Bruno Lang
SIGKDD
2000
237views more  SIGKDD 2000»
13 years 7 months ago
The UCI KDD Archive of Large Data Sets for Data Mining Research and Experimentation
Advances in data collection and storage have allowed organizations to create massive, complex and heterogeneous databases, which have stymied traditional methods of data analysis....
Stephen D. Bay, Dennis F. Kibler, Michael J. Pazza...
IRMA
2000
13 years 8 months ago
A survey of spatial data mining methods databases and statistics point of views
This paper reviews the data mining methods that are combined with Geographic Information Systems (GIS) for carrying out spatial analysis of geographic data. We will first look at d...
Karine Zeitouni
KDD
1995
ACM
95views Data Mining» more  KDD 1995»
13 years 11 months ago
Limits on Learning Machine Accuracy Imposed by Data Quality
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...
HIPC
1999
Springer
13 years 11 months ago
High Performance Data Mining
Abstract. Recent times have seen an explosive growth in the availability of various kinds of data. It has resulted in an unprecedented opportunity to develop automated data-driven ...
Vipin Kumar, Jaideep Srivastava