Criteria for evaluating the performance of a classifier are an important part in its design. They
allow to estimate the behavior of the generated classifier on unseen data and can be also …

Protein function prediction is a major challenge in the field of bioinformatics which aims at
predicting the functions performed by a known protein. Many protein data forms like protein …

This paper presents a systematic analysis of twenty four performance measures used in the
complete spectrum of Machine Learning classification tasks, ie, binary, multi-class, multi …

In this survey we discuss the task of hierarchical classification. The literature about this field
is scattered across very different application domains and for that reason research in one …

Motivation The prevalence of high-throughput experimental methods has resulted in an
abundance of large-scale molecular and functional interaction networks. The connectivity of …

Hierarchy is a natural representation of semantic taxonomies including the ones routinely
used in image segmentation. Indeed recent work on semantic segmentation reports …

The classification of high-dimensional tasks remains a significant challenge for machine
learning algorithms. Feature selection is considered to be an indispensable preprocessing …

Today machine learning methods are commonly deployed for bacterial species identification
using MALDI-TOF mass spectrometry data. However, most of the studies reported in …

Gene function prediction is a complex computational problem, characterized by several
items: the number of functional classes is large, and a gene may belong to multiple classes; …

Motivation: Systematically predicting gene (or protein) function based on molecular
interaction networks has become an important tool in refining and enhancing the existing …