Consensus function based on multi-layer networks technique

One of the great aspirations of machine learning is the clustering methods. It consists on categorized a set of similar data into different groups based on related properties. The clustering ensemble is used in aim to improve the performance and the stability of the unsupervised classification methods through the concept of weighting. One of the major problems in clustering ensembles is the consensus function. In this paper, we study the amalgamation of clustering techniques, trying to benefit from the strengths of each algorithm and we emerge the problem of combining multiple clustering of a set of objects. A new efficient for Consensus Functions of Cluster Ensembles is proposed based on Multi-layer networks technique. Experiments are carried out on a variety of datasets which highlights our proposed method.