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» Evaluating learning algorithms and classifiers
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SIGIR
2010
ACM
14 years 11 months ago
Temporally-aware algorithms for document classification
Automatic Document Classification (ADC) is still one of the major information retrieval problems. It usually employs a supervised learning strategy, where we first build a classif...
Thiago Salles, Leonardo C. da Rocha, Gisele L. Pap...
ICML
2004
IEEE
16 years 5 months ago
Lookahead-based algorithms for anytime induction of decision trees
The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...
Saher Esmeir, Shaul Markovitch
CVPR
2004
IEEE
15 years 8 months ago
Parts-Based 3D Object Classification
This paper presents a parts-based method for classifying scenes of 3D objects into a set of pre-determined object classes. Working at the part level, as opposed to the whole objec...
Daniel F. Huber, Anuj Kapuria, Raghavendra Donamuk...
BIBE
2007
IEEE
124views Bioinformatics» more  BIBE 2007»
15 years 10 months ago
Finding Cancer-Related Gene Combinations Using a Molecular Evolutionary Algorithm
—High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray ana...
Chan-Hoon Park, Soo-Jin Kim, Sun Kim, Dong-Yeon Ch...
SDM
2010
SIAM
184views Data Mining» more  SDM 2010»
15 years 5 months ago
A Robust Decision Tree Algorithm for Imbalanced Data Sets
We propose a new decision tree algorithm, Class Confidence Proportion Decision Tree (CCPDT), which is robust and insensitive to class distribution and generates rules which are st...
Wei Liu, Sanjay Chawla, David A. Cieslak, Nitesh V...