Comparing the Performance of Predictive Models Constructed Using the Techniques of Feed-Forword and Generalized Regression Neural Networks

• 主要な著者: Ajiboye, Adeleke Raheem, Ruzaini, Abdullah Arshah, Hongwu, Qin, Jamila, Abdul Hadi
• フォーマット: 論文
• 言語: English; English
• 出版事項: Penerbit UMP 2016
• 主題: QA76 Computer software
• オンライン･アクセス: http://umpir.ump.edu.my/id/eprint/13837/1/Comparing%20The%20Performance%20Of%20Predictive%20Models%20Constructed%20Using%20The%20Techniques%20Of%20Feed-Forword%20And%20Generalized%20Regression%20Neural%20Networks.pdf; http://umpir.ump.edu.my/id/eprint/13837/7/fskkp-2016-ajiboye-Comparing%20The%20Performance%20Of%20Predictive.pdf; http://umpir.ump.edu.my/id/eprint/13837/; http://ijsecs.ump.edu.my/images/archive/vol2/0017.pdf

Artificial Neural Network (ANNs) is an efficient machine learning method that can be used to fits model from data for prediction purposes. It is capable of modelling the class prediction as a nonlinear combination of the inputs. However, a number of factors may affect the accuracy of the model crea...