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» Evaluating algorithms that learn from data streams
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SAC
2004
ACM
15 years 9 months ago
Forest trees for on-line data
This paper presents an hybrid adaptive system for induction of forest of trees from data streams. The Ultra Fast Forest Tree system (UFFT) is an incremental algorithm, with consta...
João Gama, Pedro Medas, Ricardo Rocha
KES
2010
Springer
15 years 2 months ago
Visualization of Text Streams: A Survey
— This work presents related areas of research, types of data collections that are visualized, technical aspects of generating visualizations, and evaluation methodologies. Exist...
Artur Silic, Bojana Dalbelo Basic
ICML
2010
IEEE
15 years 5 months ago
Online Streaming Feature Selection
We study an interesting and challenging problem, online streaming feature selection, in which the size of the feature set is unknown, and not all features are available for learni...
Xindong Wu, Kui Yu, Hao Wang, Wei Ding
AMAI
2008
Springer
15 years 4 months ago
Bayesian learning of Bayesian networks with informative priors
This paper presents and evaluates an approach to Bayesian model averaging where the models are Bayesian nets (BNs). Prior distributions are defined using stochastic logic programs...
Nicos Angelopoulos, James Cussens
ICML
2005
IEEE
16 years 4 months ago
ROC confidence bands: an empirical evaluation
This paper is about constructing confidence bands around ROC curves. We first introduce to the machine learning community three band-generating methods from the medical field, and...
Sofus A. Macskassy, Foster J. Provost, Saharon Ros...