Overview
Consensus clustering is a technique used in data mining to group data points together that have similar characteristics. It is a powerful tool for identifying patterns in large datasets and helps to reduce the computational cost of data analysis. It can be used to identify potential relationships between data points, discover patterns in gene expression, and identify clusters of similar objects in an image. Consensus clustering is also used in machine learning applications to perform unsupervised learning and to improve the accuracy of classification algorithms. In addition, consensus clustering can help to reduce the risk of bias by averaging out the results of different clustering algorithms.
Research published in this journal
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