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Several non-supervised machine learning methods have been used in the analysis of gene expression data obtained from microarray experiments. Recently, biclustering, a non-supervised approach that performs simultaneous clustering on the row and column dimensions of the data matrix, has been shown to be remarkably effective in a variety of applications. The discovery of biclusters, which denote groups...
Clustering is a method of unsupervised learning, and a common technique for statistical data analysis used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics a novel algorithm based on clustering to extract rules from neural networks is proposed. After neural networks have been trained and pruned successfully, inner-rules are generated by...
Clustering description problem is one of key issues of the traditional document clustering algorithm. The traditional document algorithm can cluster the objects, but it can not give concept description for the clustered results. Document clustering description is a problem of labeling the clustered results of document collection clustering. It can help users determine whether one of the clusters is...
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