Machine learning in geosciences and remote sensing
The University of Texas at Dallas · Michigan State University · +2 more institutions
Abstract
Learning incorporates a broad range of complex procedures. Machine learning (ML) is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine readable data. ML covers main domains such as data mining, difficult-to-program applications, and software applications. It is a collection of a variety of algorithms (e.g. neural networks, support vector machines, self-organizing map, decision trees, random forests, case-based reasoning, genetic programming, etc.) that can provide multivariate, nonlinear, nonparametric regression or classification. The modeling capabilities of the ML-based methods have resulted in their…
Citation impact
- FWCI
- 28.46
- Percentile
- 100%
- References
- 95
Authors
4Topics & keywords
- Computer science
- Machine learning
- Genetic programming
- Artificial intelligence
- Process (computing)
- Artificial neural network
- Support vector machine
- Variety (cybernetics)