With the integration of the KEGG and Predictome databases as well as two search engines for coexpressed genes/proteins using data sets obtained from the Stanford Microarray Databa...
Zhenjun Hu, David M. Ng, Takuji Yamada, Chunnuan C...
Quantization of continuous variables is important in data analysis, especially for some model classes such as Bayesian networks and decision trees, which use discrete variables. Of...
Abstract-- This study deals with investigating the classification performance of information-theoretic measures when applied to complex biological networks. In particular, our aim ...
Laurin A. J. Mueller, Karl G. Kugler, Andreas Dand...
We propose a unified data modeling approach that is equally applicable to supervised regression and classification applications, as well as to unsupervised probability density func...
Classification has been commonly used in many data mining projects in the financial service industry. For instance, to predict collectability of accounts receivable, a binary clas...