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» CLOUDS: A Decision Tree Classifier for Large Datasets
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SAC
2004
ACM
15 years 3 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
BIBM
2010
IEEE
139views Bioinformatics» more  BIBM 2010»
14 years 7 months ago
Scalable, updatable predictive models for sequence data
The emergence of data rich domains has led to an exponential growth in the size and number of data repositories, offering exciting opportunities to learn from the data using machin...
Neeraj Koul, Ngot Bui, Vasant Honavar
CMG
2001
14 years 11 months ago
Effective Use of the KDD Process and Data Mining for Computer Performance Professionals
- The KDD (Knowledge Discovery in Databases) paradigm is a step by step process for finding interesting patterns in large amounts of data. Data mining is one step in the process. T...
Susan P. Imberman
CIDM
2009
IEEE
15 years 4 months ago
An empirical study of bagging and boosting ensembles for identifying faulty classes in object-oriented software
—  Identifying faulty classes in object-oriented software is one of the important software quality assurance activities. This paper empirically investigates the application of t...
Hamoud I. Aljamaan, Mahmoud O. Elish
BMCBI
2006
137views more  BMCBI 2006»
14 years 9 months ago
A classification-based framework for predicting and analyzing gene regulatory response
Background: We have recently introduced a predictive framework for studying gene transcriptional regulation in simpler organisms using a novel supervised learning algorithm called...
Anshul Kundaje, Manuel Middendorf, Mihir Shah, Chr...