Multiclass relevance units machine: benchmark evaluation and application to small ncRNA discovery.

ABSTRACT:

Background

Classification is the problem of assigning each input object to one of a finite number of classes. This problem has been extensively studied in machine learning and statistics, and there are numerous applications to bioinformatics as well as many other fields. Building a multiclass classifier has been a challenge, where the direct approach of altering the binary classification algorithm to accommodate more than two classes can be computationally too expensive. Hence the indirect approach of using binary decomposition has been commonly used, in which retrieving the class posterior probabilities from the set of binary posterior probabilities given by the individual binary classifiers has been a major issue.

Methods

In this work, we present an extension of a recently

SUBMITTER: Menor M 

PROVIDER: S-EPMC3582431 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature