Table 9.

Statistical analysis methods on the selected datasets [31,32,39].

Type	Name	Optimization Method
Classification	SVM (kernel = linear or rbf)	Gradient descent
Classification	Naïve Bayes	Gradient descent
Classification	Decision Tree (entropy or gini)	Information Gain, Gini
Classification	Logistic	Gradient descent
Classification	KNN	Gradient descent
Classification	Random Forest (RF)	Ensemble
Calibration Classification	Calibrated Classifier (CV)	Probability (sigmoid, isotonic)
Regression	Linear Regression	Gradient descent
Regression	KNeighbors Regressor	Gradient descent
Regression	Support Vector Regressor	Gradient descent
Regression	Decision Tree Regressor	Gain, Gini
Regression	Random Forest Regressor	Ensemble
Regression	Bayesian Regressor	Gradient descent
Regularization	Lasso (L1), Ridge (L2)	Gradient descent