Comparative Evaluation of Prediction Algorithms
CoEPrA (Comparative Evaluation of Prediction Algorithms) is a
modeling competition organized
to provide an objective testing for various classification and regression
algorithms via the process of blind prediction.
The problems proposed in the CoEPrA experiment are selected
from cheminformatics, drug design, QSAR, bioinformatics, computational
biology, medicine, toxicology, microarray gene expression data, and proteomics.
The goal of the CoEPrA competition is to advance the algorithms
and software for modeling chemical, biological, and medical data, with special
emphasis on the prediction of physico-chemical properties and biological activities
from molecular descriptors derived from the chemical structure.
In addition, CoEPrA will provide a reference database of modeling datasets that
can be used to validate and compare new classification and regression
In each CoEPrA task the participants receive a calibration dataset and
a prediction dataset.
The model (classification or regression) derived from the calibration dataset
is used to predict the dependent variable of the prediction dataset.
These predictions must be deposited before the deadline of each task.
The Organizers and Evaluators for each CoEPrA task will evaluate all
predictions and will anounce the ranking of the participants.