The nature of statistical learning theory
The nature of statistical learning theory
Machine Learning
Data mining: concepts and techniques
Data mining: concepts and techniques
When Is ''Nearest Neighbor'' Meaningful?
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Voting-Merging: An Ensemble Method for Clustering
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Combining Multiple Weak Clusterings
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
IEEE Transactions on Knowledge and Data Engineering
Data Mining for Business Applications: Introduction
Proceedings of the 2010 conference on Data Mining for Business Applications
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In Criminology research the question arises if certain types of delinquents can be identified from data, and while there are many cases that can not be clearly labeled, overlapping taxonomies have been proposed in [1,2,3]. In a recent study Juvenile offenders (N = 1572) from three state systems were assessed on a battery of criminogenic risk and needs factors and their official criminal histories. Cluster analysis methods were applied. One problem we encountered is the large number of hybrid cases that have to belong to two or more classes. To eliminate these cases we propose a method that combines the results of Bagged K-Means and the consistency method [4], a semi-supervised learning technique. A manual interpretation of the results showed very interpretable patterns that were linked to existing criminologic research.