Benchmarking Multi-Rate Codon Models

Benchmarking Multi-Rate Codon Models

The single rate codon model of non-synonymous substitution is ubiquitous in phylogenetic modeling. Indeed, the use of a non-synonymous to synonymous substitution rate ratio parameter has facilitated the interpretation of selection pressure on genomes. Although the single rate model has achieved wide acceptance, we argue that the assumption of a single rate of non-synonymous substitution is biol...

Benchmarking the effective literacy rate

By now the importance of literacy in the process of development is widely accepted. However, unlike measuring welfare or inequality, the problem of literacy measurement remains largely unexamined. Alternatives to the standard literacy rate, R, equal to the number of literate adults as a percentage of the adult population, are not well known, but this measure has its deficiencies. In particular,...

Engset multi-rate state-dependent loss models

Call blocking probabilities (CBP) are a key index of quality of service assessment in multi-rate networks. We focus on the CBP calculation in single link loss models where calls of each service-class come from finite sources and compete for the available link bandwidth under the complete sharing policy. We review the Engset multirate loss model (EnMLM) and the single-retry loss model for finite...

Towards Benchmarking Multi-Model Databases

Benchmarking Multi-label Classification Algorithms

Multi-label classification is an approach to classification problems that allows each data point to be assigned to more than one class at the same time. Real life machine learning problems are often multi-label in nature—for example image labelling, topic identification in texts, and gene expression prediction. Many multi-label classification algorithms have been proposed in the literature and,...