Table 2. Types of machine learning.

Machine learning algorithms	Description	Types
Supervised learning 30, 31	Dataset contains labels and outcomes	This includes logistic regression, Bayesian network, random forests, elastic net regression, and least absolute shrinkage and selection operator (LASSO) regression.
Unsupervised learning 30, 31	The algorithm deciphers relationships in datasets without labels.	This includes K-means clustering, hierarchical clustering, and principal component analysis.
Semi-supervised learning 30, 31	Dataset contains labeled and unlabeled classes and outcomes.	It is a mixture of supervised and unsupervised learning, used in speech and image recognition.
Re-enforcement learning 30, 31	Similar to psychology, uses reward function	Based on human psychology. Used in analytics, imaging, and disease screening