When Is ''Nearest Neighbor'' Meaningful?
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Cluster-preserving Embedding of Proteins
Cluster-preserving Embedding of Proteins
K-Landmarks: distributed dimensionality reduction for clustering quality maintenance
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
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Due to the vast amount and pace of high-dimensional data production, dimensionality reduction emerges as an important requirement in many application areas. In this paper, we introduce X-SDR, a prototype designed specifically for the deployment and assessment of dimensionality reduction techniques. X-SDR is an integrated environment for dimensionality reduction and knowledge discovery that can be effectively used in the data mining process. In the current version, it supports communication with different database management systems and integrates a wealth of dimensionality reduction algorithms both distributed and centralized. Additionally, it interacts with Weka thus enabling the exploitation of the data mining algorithms therein. Finally, X-SDR provides an API that enables the integration and evaluation of any dimensionality reduction algorithm.