The DOI matches its Crossref record; 101 of the 101 references it cites were found in a registry or an index.
Recent advances in decision trees: an updated survey
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Citations
Cites
The Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970
Quinlan, J. R. (1986) · Machine Learning · doi:10.1007/bf00116251 · Cited by 21,439
Mastering the game of Go with deep neural networks and tree search
Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., van den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., et al. (2016) · Nature · doi:10.1038/nature16961 · Cited by 15,612
Advances in neural information processing systems 7
(1996) · Computers & Mathematics with Applications · doi:10.1016/s0898-1221(96)90463-0 · Cited by 14,281
Extreme learning machine: Theory and applications
Huang, G.-B., Zhu, Q.-Y., & Siew, C.-K. (2006) · Neurocomputing · doi:10.1016/j.neucom.2005.12.126 · Cited by 13,285
Proceedings of the 24th international conference on Machine learning
(2007) · doi:10.1145/1273496 · Cited by 11,630
Classification And Regression Trees
Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (2017) · doi:10.1201/9781315139470 · Cited by 11,417
An Introduction to Genetic Algorithms
Mitchell, M. (1996) · doi:10.7551/mitpress/3927.001.0001 · Cited by 11,340
Rudin, C. (2019) · Nature Machine Intelligence · doi:10.1038/s42256-019-0048-x · Cited by 10,561
Machine learning: Algorithms, real-world applications and research directions
Sarker, I. H. (2021) · SN Computer Science · doi:10.1007/s42979-021-00592-x · Cited by 5,583 · cited 1×
“Underlying these results is not only an abundance of available data, but also important advances in the learning models themselves (Sarker 2021).”
Background
Cited by
A Survey of Decision Trees: Concepts, Algorithms, and Applications
Mienye, I. D., & Jere, N. (2024) · IEEE Access · doi:10.1109/access.2024.3416838 · Cited by 353
Generative Artificial Intelligence in Education: Advancing Adaptive and Personalized Learning
Guettala, M., Bourekkache, S., Kazar, O., & Harous, S. (2024) · Acta Informatica Pragensia · doi:10.18267/j.aip.235 · Cited by 218
Mienye, I. D., Obaido, G., Jere, N., Mienye, E., Aruleba, K., Emmanuel, I. D., & Ogbuokiri, B. (2024) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2024.101587 · Cited by 212
The empirical status of predictive coding and active inference
Hodson, R., Mehta, M., & Smith, R. (2024) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2023.105473 · Cited by 69
Integrating machine learning to advance epitope mapping
Grewal, S., Hegde, N., & Yanow, S. K. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1463931 · Cited by 35
Metadata
- Authors
- Costa, V. G., & Pedreira, C. E.
- Venue
- Artificial Intelligence Review
- Published
- 2022-10-10
- Volume
- 56
- Issue
- 5
- Pages
- 4765-4800
- ISSN
- 0269-2821 (ISSN-L)
- 1573-7462
- OpenAlex
- W4304098281
- Cited by
- 572
- References
- 101
- FWCI
- 110.18
- Type
- journal article
- Language
- en
- Open access
- closed
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- Costa, V. G., & Pedreira, C. E. (2023). Recent advances in decision trees: an updated survey. Artificial Intelligence Review. https://doi.org/10.1007/s10462-022-10275-5
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.