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» A Bayesian Metric for Evaluating Machine Learning Algorithms
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KDD
2009
ACM
156views Data Mining» more  KDD 2009»
16 years 1 months ago
Effective multi-label active learning for text classification
Labeling text data is quite time-consuming but essential for automatic text classification. Especially, manually creating multiple labels for each document may become impractical ...
Bishan Yang, Jian-Tao Sun, Tengjiao Wang, Zheng Ch...
92
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FSKD
2006
Springer
124views Fuzzy Logic» more  FSKD 2006»
15 years 4 months ago
An Effective Combination of Multiple Classifiers for Toxicity Prediction
This paper presents an investigation into the combination of different classifiers for toxicity prediction. These classification methods involved in generating classifiers for comb...
Gongde Guo, Daniel Neagu, Xuming Huang, Yaxin Bi
102
Voted
GECCO
2007
Springer
235views Optimization» more  GECCO 2007»
15 years 6 months ago
Expensive optimization, uncertain environment: an EA-based solution
Real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function e...
Maumita Bhattacharya
127
Voted
ECML
2007
Springer
15 years 6 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...
111
Voted
ICML
2010
IEEE
15 years 1 months ago
Non-Local Contrastive Objectives
Pseudo-likelihood and contrastive divergence are two well-known examples of contrastive methods. These algorithms trade off the probability of the correct label with the probabili...
David Vickrey, Cliff Chiung-Yu Lin, Daphne Koller