The goal of clustering is to identify distinct groups in a dataset. Compared to non-parametric clustering methods like complete linkage, hierarchical model-based clustering has th...
We focus on the problem of efficient learning of dependency trees. Once grown, they can be used as a special case of a Bayesian network, for PDF approximation, and for many other u...
Evolutionary Clustering has emerged as an important research topic in recent literature of data mining, and solutions to this problem have found a wide spectrum of applications, p...
Tianbing Xu, Zhongfei (Mark) Zhang, Philip S. Yu, ...
Mining association rules may generate a large numbers of rules making the results hard to analyze manually. Pasquier et al. have discussed the generation of GuiguesDuquenne–Luxe...
Abstract. E cient data mining algorithms are crucial fore ective knowledge discovery. We present the Multi-Stream Dependency Detection (msdd) data mining algorithm that performs a ...