Effort prediction is a very important issue for software project management. Historical project data sets are frequently used to support such prediction. But missing data are oft...
Missing data is a widespread problem that can affect the ability to use data to construct effective prediction systems. We investigate a common machine learning technique that can...
Qinbao Song, Martin J. Shepperd, Xiangru Chen, Jun...
Background: The popularity of massively parallel exome and transcriptome sequencing projects demands new data mining tools with a comprehensive set of features to support a wide r...
Background: Modeling of gene expression data from time course experiments often involves the use of linear models such as those obtained from principal component analysis (PCA), i...
Peter D. Wentzell, Tobias K. Karakach, Sushmita Ro...
Summary: The MolClass toolkit and data portal generates computational models from user-defined small molecule datasets based on structural features identified in hit and non-hit m...