The problem of graph classification has attracted great interest in the last decade. Current research on graph classification assumes the existence of large amounts of labeled tra...
Traditional feature selection methods assume that the data are independent and identically distributed (i.i.d.). In real world, tremendous amounts of data are distributed in a net...
Background: Activities of drug molecules can be predicted by QSAR (quantitative structure activity relationship) models, which overcomes the disadvantages of high cost and long cy...
Guo-Zheng Li, Hao-Hua Meng, Mary Qu Yang, Jack Y. ...
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Variable selection for cluster analysis is a difficult problem. The difficulty originates not only from the lack of class information but also the fact that high-dimensional data ...
Leonard K. M. Poon, Nevin Lianwen Zhang, Tao Chen,...