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» Coactive Learning for Distributed Data Mining
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HIPC
1999
Springer
15 years 2 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
ICDM
2006
IEEE
130views Data Mining» more  ICDM 2006»
15 years 3 months ago
Boosting for Learning Multiple Classes with Imbalanced Class Distribution
Classification of data with imbalanced class distribution has posed a significant drawback of the performance attainable by most standard classifier learning algorithms, which ...
Yanmin Sun, Mohamed S. Kamel, Yang Wang 0007
ICDM
2007
IEEE
158views Data Mining» more  ICDM 2007»
15 years 4 months ago
On Appropriate Assumptions to Mine Data Streams: Analysis and Practice
Recent years have witnessed an increasing number of studies in stream mining, which aim at building an accurate model for continuously arriving data. Somehow most existing work ma...
Jing Gao, Wei Fan, Jiawei Han
KDD
1998
ACM
250views Data Mining» more  KDD 1998»
15 years 2 months ago
Data Mining for Direct Marketing: Problems and Solutions
Direct marketing is a process of identifying likely buyers of certain products and promoting the products accordingly. It is increasingly used by banks, insurance companies, and t...
Charles X. Ling, Chenghui Li
KDD
1997
ACM
184views Data Mining» more  KDD 1997»
15 years 1 months ago
JAM: Java Agents for Meta-Learning over Distributed Databases
In this paper, we describe the JAM system, a distributed, scalable and portable agent-based data mining system that employs a general approach to scaling data mining applications ...
Salvatore J. Stolfo, Andreas L. Prodromidis, Shell...