The purpose of this thesis is to develop new regular and feature selection-based models for predicting the racing times of cross-country skiers by using machine learning and feature selection methods. Particularly, six popular machine learning methods including Optimized-General Regression Neural Network (OPGRNN), General Regression Neural Network (GRNN), Support Vector Machine (SVM), Multilayer Perceptron (MLP), Radial Basis Function Neural Network (RBFNN), and Single Decision Tree (SDT) have been used, whereas Relief-F has been employed as the feature selector. Several models have been...
The purpose of this thesis is to develop new regular and feature selection-based models for predicting the racing times of cross-country skiers by usi...
