Review Article

Computational Intelligence in Sports: A Systematic Literature Review

Table 8

Algorithms.

Paper Algorithm

[27] Artificial Neural Networks, Statistical Classifiers and Hidden Markov Models.

[23] C4.5, Random Forest and Native Bayes Tree.

[33] Differential Evolution.

[31] k-means, Ant Colony Optimization.

[35] Naive Bayes.

[37] Particle Swarm Optimization.

[47] -

[49] Bat Algorithm.

[39] Particle Swarm Optimization.

[41] K-Means.

[43] Artificial Neural Networks.

[45] AISReact.

[24] Association Rule Mining Algorithms.

[53] Association Rule Mining Algorithms.

[51] Inductive Logic Programming

[36] Gaussian Naive Bayes, Support Vector Machine and Random Forest.

[30] Random Forest and Classification and Regression Trees.

[38] Linear Algebra Methods, Artificial Neural Networks and Random Forest.

[40] Decision tree, Artificial Neural Networks and Support Vector Machine.

[42] Naive Bayes, Decision tree, Support Vector Machine and K Nearest Neighbors.

[28] Naive Bayes, Support Vector Machine and Random Forest.

[32] Random Forest.

[26] K-means.

[34] Artificial Neural Networks.

[25] Hierarchical Clustering.

[44] Artificial Neural Networks.

[29] Particle Swarm Optimization, Support Vector Machine, C4.5.

[52] Bayesian Belief Networks, Naive Bayes and K-means.

[46] Random Forest.

[48] -

[50] -