Search
Now showing items 1-2 of 2
Efficient learning of decomposable models with a bounded clique size
(2014-05-08)
The learning of probability distributions from data is a ubiquitous problem in the fields of Statistics and Artificial Intelligence. During the last decades several learning algorithms have been proposed to learn probability ...
A sensitivity study of bias and variance of k-fold cross-validation in prediction error estimation
(2009)
In the machine learning field the performance of a classifier is usually measured in terms of prediction error. In most real-world problems, the error cannot be exactly calculated and it must be estimated. Therefore, it’s ...