Table 3.

Machine Learning Methods.

Type of Machine Learning	Description of Technique
Unsupervised Learning	Hidden patters within unlabeled datasets are identified through clustering or association (C-means, K-means, etc)
Reinforcement Learning	Sequential feedback is provided to models based on their response to training data (Q-learning, SARSA, etc)
Semi-Supervised Learning	Models are trained with a small amount of initial data before being used to identify structures within larger unlabeled datasets (Generative model, semi-supervised SVM, etc).
Supervised Learning	Labeled inputs and outputs are used to approximate a relationship between variables (ie linear regression, logistic regression, SVM, KNN, etc).

Definitions of Machine Learning Techniques and Sample Methods. Techniques are shortened to SARSA (State, Action, Reward, State, Action), SVM (Support Vector Machine), and KNN (K Nearest Neighbor).