Abstract Irregularities are widespread in large databases and often lead to erroneous conclusions with respect to data mining and statistical analysis. For example, considerable bi...
Siu-Tong Au, Rong Duan, Siamak G. Hesar, Wei Jiang
We present an application of inductive concept learning and interactive visualization techniques to a large-scale commercial data mining project. This paper focuses on design and c...
William H. Hsu, Michael Welge, Thomas Redman, Davi...
In this paper, we propose a distributed solution to the problem of configuring classifier trees in distributed stream mining systems. The configuration involves selecting appro...
Hyunggon Park, Deepak S. Turaga, Olivier Verscheur...
Through the algorthmic design patterns of data parallelism and task parallelism, the graphics processing unit (GPU) offers the potential to vastly accelerate discovery and innovat...
Jeremy S. Archuleta, Yong Cao, Thomas Scogland, Wu...
We present two efficient Apriori implementations of Frequent Itemset Mining (FIM) that utilize new-generation graphics processing units (GPUs). Our implementations take advantage ...