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ICML
2005
IEEE
16 years 2 months ago
Reducing overfitting in process model induction
In this paper, we review the paradigm of inductive process modeling, which uses background knowledge about possible component processes to construct quantitative models of dynamic...
Will Bridewell, Narges Bani Asadi, Pat Langley, Lj...
ICML
2005
IEEE
16 years 2 months ago
Using additive expert ensembles to cope with concept drift
We consider online learning where the target concept can change over time. Previous work on expert prediction algorithms has bounded the worst-case performance on any subsequence ...
Jeremy Z. Kolter, Marcus A. Maloof
ECML
2007
Springer
15 years 7 months ago
Generalization-Based Similarity for Conceptual Clustering
The availability of techniques for comparing descriptions has many applications in Artificial Intelligence, ranging from description selection to flexible matching, from instance...
Stefano Ferilli, Teresa Maria Altomare Basile, Nic...
ML
2006
ACM
15 years 1 months ago
Gleaner: Creating ensembles of first-order clauses to improve recall-precision curves
Many domains in the field of Inductive Logic Programming (ILP) involve highly unbalanced data. A common way to measure performance in these domains is to use precision and recall i...
Mark Goadrich, Louis Oliphant, Jude W. Shavlik
NIPS
2004
15 years 2 months ago
Confidence Intervals for the Area Under the ROC Curve
In many applications, good ranking is a highly desirable performance for a classifier. The criterion commonly used to measure the ranking quality of a classification algorithm is ...
Corinna Cortes, Mehryar Mohri