… We propose a neural regression tree model for RvC. In this model, we employ a joint … in the
tree. We empirically show the validity of our model by testing it on two challenging regression …

… is that the tree structure is transparent, which in comparison with artificial neural networks
(… can be distinguished within DT: classification trees and regression trees (RT). This section …

In this study, performances of classification techniques were compared in order to predict
the presence of coronary artery disease (CAD). A retrospective analysis was performed in …

… Neural Networks (NNs) models are available in the literature, however, very few involved
Classification and Regression Tree (… accuracy involving nonlinear regression, NNs and CART …

… of artificial neural networks (ANN) and regression trees technique along with the … regression
trees technique, which were then compared to those built by multiple nonlinear regression …

… The resulting classification or regression tree can be considered to be a neural network in
which the weights are not learned during training but rather it is the structure of the network …

… Most of these decision aids consist of nomograms, artificial neural networks (ANNs), look-up
tables, classification and regression tree analyses (CART) and risk group stratification (RGS…

… combine the advantages of regression tree and artificial neural network. The hypothesis …
determined by using the regression tree technique and used in artificial neural networks. The …

… Artificial neural networks (ANNs) and classification and regression trees (CARTs) have …
accuracy of three different methodologies (ie logistic regression, ANNs and CARTs) for the …

… CART used was the regression tree instead of the classification tree. At a … regression trees
of the CART algorithm were as accurate as predictions based on the conventional regression …