We put forward a new method of growing regression trees via maximum likelihood. It inherits the CART (Brieman et al., 1984) backward fitting idea. However, standard likelihood based methods such as model selection criteria and likelihood ratio tests are naturally incorporated into each stage of the tree procedure. Compared with other least squared tree methods, maximum likelihood regression tre...

The regression tree [1] has been used as a tool for exploring multivariate data sets for some time. As in multiple linear regression, the technique is applied to a data set consisting of a continuous response variable y and a set of predictor variables {x1, x2, ..., xk} which may be continuous or categorical. However, instead of modelling y as a linear function of the predictors, regression tre...

In many real-world domains the task of machine learning algorithms is to learn a theory predicting numerical values. In particular several standard test domains used in Inductive Logic Programming (ILP) are concerned with predicting numerical values from examples and relational and mostly non-determinate background knowledge. However, so far no ILP algorithm except one can predict numbers and c...

A method of combining three analytic techniques including regression rule induction, the k-nearest neighbors method and time series forecasting by means of the ARIMA methodology is presented. A decrease in the forecasting error while solving problems that concern natural hazards and machinery monitoring in coal mines was the main objective of the combined application of these techniques. The M5...

We study intersecting noncommutative (NC) M5-branes from κ-invariance of an open supermembrane action with constant three-form fluxes. The κ-invariance gives rise to possible D-brane configurations for which projection operators can be determined. We construct projection operators for two types of 1/4 BPS intersecting NC M5-branes. The one is an intersection of two NC M5-branes: NC M5⊥NC M5 (3)...