This paper presents a new supervised clustering method The algorithm is based on the information related t o both the global and local distributions of training samples,avoiding the expensive computation and local minimum of traditional neural networks Unknow n patterns can also be recognized The simulation results demonstrate the soun dness of this approac

Novel semi-supervised clustering:collaborating primary space with auxiliary space;

Research on the Present Situation of Semi-Supervised Clustering Algorithm

Some Developments on Semi-Supervised Clustering

A new method based on unsupervised clustering for lithium-ion battery classification;

A background sub-set was obtained from the data set by unsupervised clustering.

The learning strategy is motivated by the statistical query model and unsupervised clustering method.

Firstly,the composite in the period of August 13 to 28 which corresponds to the greenest image of the year was segmented with unsupervised clustering algorithm.

Objective evaluation system of garment seam based on supervised fuzzy clustering;

A new method for fast building the rough data model (RDM) by means of supervised fuzzy clustering in the product space of input and output variables is proposed.

To evaluate the sewing ability of the fabric objectively before being garment,a prediction system based on supervised fuzzy clustering neural network(SFCNN) for garment seams is proposed.