Table 1.

Different machine learning categories

	Supervised learning	Unsupervised learning	Reinforcement learning
Dataset	Labeled (input and output are known)	Unlabeled (output is not known)	No predefined data
Method	Analyze the relation between input and output. The output is predicted based on this relation	Analyze the input parameters to uncover hidden patterns. Output is predicted based on those patterns	Randomly trialing a vast number of possible inputs, then comparing and grading their performance
Example	Decision trees, support vector machines, neutral networks, k-nearest neighbors	k-means clustering, archetype analysis	Q-learning