Related references
Note: Only part of the references are listed.A Comparison of MCC and CEN Error Measures in Multi-Class Prediction
Giuseppe Jurman et al.
PLOS ONE (2012)
Data Balancing for Efficient Training of Hybrid ANN/HMM Automatic Speech Recognition Systems
Ana Isabel Garcia-Moral et al.
IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING (2011)
Fish recruitment prediction, using robust supervised classification methods
Jose A. Fernandes et al.
ECOLOGICAL MODELLING (2010)
A novel measure for evaluating classifiers
Jin-Mao Wei et al.
EXPERT SYSTEMS WITH APPLICATIONS (2010)
Two information-theoretic tools to assess the performance of multi-class classifiers
Francisco J. Valverde-Albacete et al.
PATTERN RECOGNITION LETTERS (2010)
Exploring the within- and between-class correlation distributions for tumor classification
Xuelian Wei et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2010)
Bayesian approach to transforming public gene expression repositories into disease diagnosis databases
Haiyan Huang et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2010)
A systematic analysis of performance measures for classification tasks
Marina Sokolova et al.
INFORMATION PROCESSING & MANAGEMENT (2009)
A lot of randomness is hiding in accuracy
Arle Ben-David
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2007)
An introduction to ROC analysis
Tom Fawcett
PATTERN RECOGNITION LETTERS (2006)
Predicting the clinical status of human breast cancer by using gene expression profiles
M West et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2001)