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Feature selection from gene expression microarray data is a widely used technique for selecting candidate genes in various cancer studies. Besides predictive ability of the selected genes, an important aspect in evaluating a selection method is the stability of the selected genes. Experts instinctively have high confidence in the result of a selection(More)
  • Yue Han, Lei Yu
  • 2010
Besides high accuracy, stability of feature selection has recently attracted strong interest in knowledge discovery from high-dimensional data. In this study, we present a theoretical framework about the relationship between the stability and accuracy of feature selection based on a formal bias-variance decomposition of feature selection error. The(More)
In this paper, we propose a sparse kernel representation classification algorithm (SKRC) for images classification and recognition. The training dictionary is composed by labeled samples directly, and both training dictionary and testing sample are mapped into feature space from original sample space by the sparse kernel which employs the(More)
In applications of Web data integration, we frequently need to identify whether data objects in different data sources represent the same entity in the real world. This problem is known as entity resolution. In this paper, we propose a generic framework for entity resolution for relational data sets, called BARM, consisting of the Blocker, Attribute(More)
A key issue, whenever people work together to solve a complex problem, is how to divide the problem into parts done by different people and combine the parts into a solution for the whole problem. This paper presents a novel way of doing this with groups of contests called contest webs. Based on the analogy of supply chains for physical products, the method(More)