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» Learning with Rare Cases and Small Disjuncts
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95
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ICML
1995
IEEE
15 years 4 months ago
Learning with Rare Cases and Small Disjuncts
Systems that learn from examples often create a disjunctive concept definition. Small disjuncts are those disjuncts which cover only a few training examples. The problem with sma...
Gary M. Weiss
SBIA
2004
Springer
15 years 5 months ago
Learning with Class Skews and Small Disjuncts
One of the main objectives of a Machine Learning – ML – system is to induce a classifier that minimizes classification errors. Two relevant topics in ML are the understanding...
Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Mar...
83
Voted
ICML
2010
IEEE
15 years 1 months ago
Unsupervised Risk Stratification in Clinical Datasets: Identifying Patients at Risk of Rare Outcomes
Most existing algorithms for clinical risk stratification rely on labeled training data. Collecting this data is challenging for clinical conditions where only a small percentage ...
Zeeshan Syed, Ilan Rubinfeld
90
Voted
ILP
2003
Springer
15 years 5 months ago
Disjunctive Learning with a Soft-Clustering Method
In the case of concept learning from positive and negative examples, it is rarely possible to find a unique discriminating conjunctive rule; in most cases, a disjunctive descripti...
Guillaume Cleuziou, Lionel Martin, Christel Vrain
MM
2005
ACM
172views Multimedia» more  MM 2005»
15 years 6 months ago
Learning the semantics of multimedia queries and concepts from a small number of examples
In this paper we unify two supposedly distinct tasks in multimedia retrieval. One task involves answering queries with a few examples. The other involves learning models for seman...
Apostol Natsev, Milind R. Naphade, Jelena Tesic