Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Logical analysis of numerical data
Mathematical Programming: Series A and B - Special issue: papers from ismp97, the 16th international symposium on mathematical programming, Lausanne EPFL
A simple, fast, and effective rule learner
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Outlier detection for high dimensional data
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Mining needle in a haystack: classifying rare classes via two-phase rule induction
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Detecting Group Differences: Mining Contrast Sets
Data Mining and Knowledge Discovery
An Implementation of Logical Analysis of Data
IEEE Transactions on Knowledge and Data Engineering
Rule Induction with CN2: Some Recent Improvements
EWSL '91 Proceedings of the European Working Session on Machine Learning
Evaluating Boosting Algorithms to Classify Rare Classes: Comparison and Improvements
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Discretization of Continuous Attributes for Learning Classification Rules
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
A MINSAT Approach for Learning in Logic Domains
INFORMS Journal on Computing
ADMIT: anomaly-based data mining for intrusions
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
CBMS '02 Proceedings of the 15th IEEE Symposium on Computer-Based Medical Systems (CBMS'02)
Editorial: special issue on learning from imbalanced data sets
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Mining with rarity: a unifying framework
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Data mining approaches for intrusion detection
SSYM'98 Proceedings of the 7th conference on USENIX Security Symposium - Volume 7
Data Mining and Knowledge Discovery via Logic-Based Methods: Theory, Algorithms, and Applications
Data Mining and Knowledge Discovery via Logic-Based Methods: Theory, Algorithms, and Applications
Analytical and numerical comparisons of biogeography-based optimization and genetic algorithms
Information Sciences: an International Journal
| Hi-index | 0.00 |
We consider a new problem of detecting members of a rare class of data, the needles, which have been hidden in a set of records, the haystack. The only information regarding the characterization of the rare class is a single instance of a needle. It is assumed that members of the needle class are similar to each other according to an unknown needle characterization. The goal is to find the needle records hidden in the haystack. This paper describes an algorithm for that task and applies it to several example cases.