Title: Binary Classification via GMDH-Type Neural Network Algorithms
Description: Performs binary classification via Group Method of Data Handling (GMDH) - type neural network algorithms. There exist two main algorithms available in GMDH() and dceGMDH() functions. GMDH() performs classification via GMDH algorithm for a binary response and returns important variables. dceGMDH() performs classification via diverse classifiers ensemble based on GMDH (dce-GMDH) algorithm. Also, the package produces a well-formatted table of descriptives for a binary response. Moreover, it produces confusion matrix, its related statistics and scatter plot (2D and 3D) with classification labels of binary classes to assess the prediction performance. All 'GMDH2' functions are designed for a binary response. See Dag O. and Yozgatligil C. (2016, ISSN:2073-4859) and Kondo T. and Ueno J. (2016, ISSN:1349-4198) for the details of GMDH algorithms.

Description: Performs binary classification via Group Method of Data Handling (GMDH) - type neural network algorithms. There exist two main algorithms available in GMDH() and dceGMDH() functions. GMDH() performs classification via GMDH algorithm for a binary response and returns important variables. dceGMDH() performs classification via diverse classifiers ensemble based on GMDH (dce-GMDH) algorithm. Also, the package produces a well-formatted table of descriptives for a binary response. Moreover, it produces confusion matrix, its related statistics and scatter plot (2D and 3D) with classification labels of binary classes to assess the prediction performance. All 'GMDH2' functions are designed for a binary response (Dag et al., 2019, <https://download.atlantis-press.com/article/125911202.pdf>).

Author: Osman Dag [aut, cre], Erdem Karabulut [aut], Reha Alpar [aut], Merve Kasikci [ctb]

Maintainer: Manuel Villacorta Tilve <mvt.oviedo@gmail.com>
Description: Regression using GMDH algorithms from Prof. Alexey G. Ivakhnenko.
Group Method of Data Handling (GMDH), or polynomial neural networks, is a family of inductive algorithms
that performs gradually complicated polynomial models and selecting the best solution by an external criterion.
In other words, inductive GMDH algorithms give possibility finding automatically interrelations in data, and
selecting an optimal structure of model or network.
The package includes GMDH Combinatorial, and GMDH MIA (Multilayered Iterative Algorithm) using PRESS (Predicted
Residual Error Sum of Squares Statistic) criteria. It is calculated as the sums of squares of the prediction
Farlow, S.J. (1981): "The GMDH algorithm of Ivakhnenko", The American Statistician, 35(4), pp. 210-215. <doi:10.2307/2683292>
Ivakhnenko A.G. (1968): "The Group Method of Data Handling - A Rival of the Method of Stochastic Approximation", Soviet Automatic Control, 13(3), pp. 43-55.