Evaluating the performance of a classification algorithm critically requires a measure of the
degree to which unseen examples have been identified with their correct class labels. In …

Motivation: Computational approaches to protein function prediction infer protein function by
finding proteins with similar sequence, structure, surface clefts, chemical properties, amino …

This research attempts to extrapolate the results of education research about computer
usage and IS research about technology acceptance to e-learning. Based on the Technology …

With the rapid change in all types of working environment, there is a need to implement
electronic learning (e-learning) systems to train people in new technologies, products, and …

The increasing wealth of biological data coming from a large variety of platforms and the
continued development of new high-throughput methods for probing biological systems require …

The fundamental mathematical tools needed to understand machine learning include linear
algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability …

Credit scoring models have been widely studied in the areas of statistics, machine learning,
and artificial intelligence (AI). Many novel approaches such as artificial neural networks (…

This paper addresses the problem of choosing a kernel suitable for estimation with a support
vector machine, hence further automating machine learning. This goal is achieved by …

We report the results of molecular analysis of 39 isolates of Cryptosporidium parvum from
human and bovine sources in nine human outbreaks and from bovine sources from a wide …

Multidimensional scaling (MDS) is a statistical tool for constructing a low-dimensional
configuration to represent the relationships between the objects. Although MDS has been widely …