Nonparametric regression models offer a way to understand and quantify relationships between variables without having identify an appropriate family of possible functions. Although many estimation methods for these have been proposed in the literature, most them can be highly sensitive presence small proportion atypical observations training set. A review outlier robust nonparametric is provide...

There are three common types of regression models: parametric, semiparametric and nonparametric regression. The model should be used to fit the real data depends on how much information is available about form relationship between response variable explanatory variables, random error distribution that assumed. Researchers need familiar with each modeling approach requirements. In this paper, di...

The rotation forest ensemble method using a genetic fuzzy rule-based system as a base learning algorithm was developed in Matlab environment. The method was applied to the real-world regression problem of predicting the prices of residential premises based on historical data of sales/purchase transactions. The computationally intensive experiments were conducted aimed to compare the accuracy of...

The ensemble machine learning methods incorporating random subspace and random forest employing genetic fuzzy rule-based systems as base learning algorithms were developed in Matlab environment. The methods were applied to the real-world regression problem of predicting the prices of residential premises based on historical data of sales/purchase transactions. The accuracy of ensembles generate...