Table 1.

Some example machine learning (ML) algorithms, ordinary parameters and hyper-parameters

ML algorithm	Example ordinary parameters	Example hyper-parameters
Random forest	Input variable and threshold value selected at every internal node of a decision tree	Number of decision trees, number of input variables to evaluate at every internal node of a decision tree
Support vector machine	Support vectors, lagrange multiplier for every support vector	Kernel to use, degree of a polynomial kernel, ε for round-off error, regularization constant C, tolerance parameter