Table 1.

Methodology of supervised and unsupervised learning within machine learning.

Machine Learning Classification	Types of Problems Each Classification Is Used for
Supervised Learning—Uses reference data to analyze algorithms and apply the algorithms to a similar dataset [3]	Classification—Utilizes an algorithm to assign a dataset into specific categories. Specifically, draws conclusions on how specific categories in the dataset should be labeled. [4]
	Regression—Analyzes the relationship between dependent and independent variables, particularly for making projections [4]
Unsupervised Learning—Identifies hidden patterns in data without any given reference [3]	Clustering—Organizes unlabeled data based on similarities and differences [5]
	Dimension Reduction—Reduces the number of data inputs while preserving the data integrity; applied when there is an increased number of features or dimensions in a dataset [5]