One-class svms for document classification
The Journal of Machine Learning Research
Estimating the Support of a High-Dimensional Distribution
Neural Computation
Extreme re-balancing for SVMs: a case study
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Utilizing hierarchical feature domain values for prediction
Data & Knowledge Engineering
Classification of Anti-learnable Biological and Synthetic Data
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
EFFECTIVENESS OF SUPPORT VECTOR MACHINE FOR CRIME HOT-SPOTS PREDICTION
Applied Artificial Intelligence
Textual information for predicting functional properties of the genes
BioNLP '08 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
SVM Based Decision Analysis and Its Granular-Based Solving
ICCSA '09 Proceedings of the International Conference on Computational Science and Its Applications: Part II
An analysis of the anti-learning phenomenon for the class symmetric polyhedron
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
On the pattern recognition and classification of stochastically episodic events
Transactions on Compuational Collective Intelligence VI
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In this paper, we outline the main steps leading to the development of the winning solution for Task 2 of KDD Cup 2002 (Yeast Gene Regulation Prediction). Our unusual solution was a pair of linear classifiers in high dimensional space (∼14,000), developed with just 38 and 84 training examples, respectively, all belonging to the target class only. The classifiers were built using the support vector machine approach outlined in the paper.