Background: Sequence-derived structural and physicochemical descriptors have frequently been used in machine learning prediction of protein functional families, thus there is a ne...
Serene A. K. Ong, Hong Huang Lin, Yu Zong Chen, Ze...
Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar ...
evel of abstraction, we can represent a workflow as a directed graph with operators (or tasks) at the vertices (see Figure 1). Each operator takes inputs from data sources or from ...
Background: The advent of the technology of DNA microarrays constitutes an epochal change in the classification and discovery of different types of cancer because the information ...
A central problem in multistrategy learning systems is the selection and sequencing of machine learning algorithms for particular situations. This is typically done by the system ...