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The decision tree classifier: Design and potential
Abstract
This paper presents the basic concepts of a multistage classification strategy called the decision tree classifier. Two methods for designing decision trees are discussed and experimental results are reported. The relative advantages and disadvantages of each design method are considered. A spectrum of typical applications in remote sensing is noted.
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Cited by
Decision tree classification of land cover from remotely sensed data
Friedl, M. A., & Brodley, C. E. (1997) · Remote Sensing of Environment · doi:10.1016/s0034-4257(97)00049-7 · Cited by 1,542
Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey
Murthy, S. K. (1998) · Data Mining and Knowledge Discovery · doi:10.1023/a:1009744630224 · Cited by 991
Understanding the Effect of Deplatforming on Social Networks
Ali, S., Saeed, M. H., Aldreabi, E., Blackburn, J., De Cristofaro, E., Zannettou, S., & Stringhini, G. (2021) · 13th ACM Web Science Conference 2021 · doi:10.1145/3447535.3462637 · Cited by 109
Machine learning for microalgae detection and utilization
Ning, H., Li, R., & Zhou, T. (2022) · Frontiers in Marine Science · doi:10.3389/fmars.2022.947394 · Cited by 83
Metadata
- Authors
- Swain, P. H., & Hauska, H.
- Venue
- IEEE Transactions on Geoscience Electronics
- Published
- 1977-07
- Volume
- 15
- Issue
- 3
- Pages
- 142-147
- ISSN
- 0018-9413 (ISSN-L)
- OpenAlex
- W1970361289
- Cited by
- 552
- References
- 0
- FWCI
- 11.61
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: The decision tree classifier: Design and potential. https://app.cochat.ai/papers/10.1109/tge.1977.6498972
- The paper
- Swain, P. H., & Hauska, H. (1977). The decision tree classifier: Design and potential. IEEE Transactions on Geoscience Electronics. https://doi.org/10.1109/tge.1977.6498972
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
