High Performance Data Mining: Scaling Algorithms, Applications and Systems brings together in one place important contributions and up-to-date research results in this fast moving area.
High Performance Data Mining: Scaling Algorithms, Applications and Systems serves as an excellent reference, providing insight into some of the most challenging research issues in the field.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Editorial; Yike Guo, R. Grossman. Parallel Formulations of Decision-Tree Classification Algorithms; A. Srivastava, Eui-Hong Han, V. Kumar, V. Singh. A Fast Parallel Clustering Algorithm for Large Spatial Databases; Xiaowei Xu, J. Jager, H.-P. Kiregel. Effect of Data Distribution in Parallel Mining of Associations; D.W. Cheung, Yongqiao Xiao. Parallel Learning of Belief Networks in Large and Difficult Domains; Y. Xiang, T. Chu.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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