The advantage of using linear regression in the leaves of a regression tree is analysed in the paper. It is carried out how this modiication aaects the construction, pruning and interpretation of a regression tree. The modiication is tested on artiicial and real-life domains. The results show that the mod-iication is beneecial as it leads to smaller classiica-tion errors of induced regression t...

Both linear neural network and multiple linear regression models can be used for multi-factor analysis and forecasting, but the data of the multiple linear regression model are required to meet such conditions as independence and normality, while the data of the linear neural network are only required to have a linear relationship. This article uses the same set of data to establish respectivel...

carbon sequestration into plants biomass, especially in fast growing trees is an easier and economically way for dropping off co2 from atmosphere. this study was carried out in order to investigate above-ground biomass of white poplar (populous alba, l.) plantations that was planted in fourdifferent plant spacing (0.5 × 0.5, 1×1, 2×2 and 4×4 m.) in chaharmahal and bakhtiari province in west of ...

Network-level multi-step road condition forecasting is an important step in accurate road maintenance planning, where correct maintenance activities are defined in place and time of road networks. Forecasting methods have developed from engineering models to non-linear machine learning methods that make use of the collected condition and traffic data of the road network. Least Squares Support V...

abstract spatial prediction of soil organic carbon is a crucial proxy to manage and conserve natural resources, monitoring co2 and preventing soil erosion strategies within the landscape, regional, and global scale. the objectives of this study was to evaluate capability of artificial neural network and multivariate linear regression models in order to predict soil organic carbon using terrain ...

histamine h3 receptor subtype has been the target of several recent drug development programs. quantitative structure-activity relationship (qsar) methods are used to predict the pharmaceutically relevant properties of drug candidates whenever it is applicable. the aim of this study was to compare the predictive powers of three different qsar techniques, namely, multiple linear regression (mlr)...

Logistic regression is a commonly used representation for aggregators in Bayesian belief networks when a child has multiple parents. In this paper we consider extending logistic regression to relational models, where we want to model varying populations and interactions among parents. In this paper, we first examine the representational problems caused by population variation. We show how these...