A Review on Machine Learning Strategies for Real-World Engineering Applications

Table 1

ML Technique varieties with approaches and examples.

Examples	Model building	Learning types	Approach
Regression, classification	Models or algorithms that use labeled data for learning	Supervised	Task-driven approach
Dimensionality reduction, association, clustering	Models or algorithms that uses unlabeled data for learning	Unsupervised	Data-driven approach
Clustering and classification	Using combined data models are built	Semi-supervised	Unlabeled + labeled
Control and classification	Using the concept of penalty and reward as a basis models are built	Reinforcement	Environment-driven approach