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» Data Mining: Machine Learning, Statistics, and Databases
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ICML
2004
IEEE
16 years 2 months ago
The Bayesian backfitting relevance vector machine
Traditional non-parametric statistical learning techniques are often computationally attractive, but lack the same generalization and model selection abilities as state-of-the-art...
Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 1 months ago
Local decomposition for rare class analysis
Given its importance, the problem of predicting rare classes in large-scale multi-labeled data sets has attracted great attentions in the literature. However, the rare-class probl...
Junjie Wu, Hui Xiong, Peng Wu, Jian Chen
KDD
2009
ACM
239views Data Mining» more  KDD 2009»
16 years 2 months ago
Tell me something I don't know: randomization strategies for iterative data mining
There is a wide variety of data mining methods available, and it is generally useful in exploratory data analysis to use many different methods for the same dataset. This, however...
Heikki Mannila, Kai Puolamäki, Markus Ojala, ...
INFORMS
2007
123views more  INFORMS 2007»
15 years 1 months ago
Constructing Ensembles from Data Envelopment Analysis
It has been shown in prior work in management science, statistics and machine learning that using an ensemble of models often results in better performance than using a single ‘...
Zhiqiang Zheng, Balaji Padmanabhan
SLP
1989
105views more  SLP 1989»
15 years 2 months ago
Automatic Ordering of Subgoals - A Machine Learning Approach
This paper describes a learning system, LASSY1, which explores domains represented by Prolog databases, and use its acquired knowledge to increase the efficiency of a Prolog inter...
Shaul Markovitch, Paul D. Scott