In flood management it is important to reliably estimate the discharge in a river. Hydrologists use historic data to establish a rating curve – a relationship between the water level (stage) and discharge. ANN and M5 model trees were used to reconstruct this relationship on an example of an Indian river. The predictive accuracy of these machine learning methods models was found to be superior t...

The application of boosting technique to regression problems has received relatively little attention in contrast to research aimed at classification problems. This letter describes a new boosting algorithm, AdaBoost.RT, for regression problems. Its idea is in filtering out the examples with the relative estimation error that is higher than the preset threshold value, and then following the Ada...

Partial 1-trees are undirected graphs of treewidth at most one. Similarly, partial 1-DAGs are directed graphs of KellyWidth at most two. It is well-known that an undirected graph is a partial 1-tree if and only if it has no K3 minor. In this paper, we generalize this characterization to partial 1-DAGs. We show that partial 1-DAGs are characterized by three forbidden directed minors, K3, N4 and M5.

Background: Due to the importance of medical studies, researchers of this field should be familiar with various types of statistical analyses to select the most appropriate method based on the characteristics of their data sets. Classification and regression trees (CARTs) can be as complementary to regression models. We compared the performance of a logistic regression model and a CART in predi...

The paper presents a new algorithm to build a feedforward neural network with a single hidden layer. The algorithm starts with 1 hidden unit and the new hidden units are added to the network only if they improve the classification accuracy of the network on the cross-validation samples. The initialization of the weights and bias is done using Nguyen-Widrow method and the network is trained with...