Machine learning: A primer
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Classification can be performed with many variables with nonlinear interactions.
“Classification can be performed with many variables with nonlinear interactions (Bzdok et al., 2018; Bzdok et al., 2017).”
From Multiclass characterization of frontotemporal dementia variants via multimodal brain network computational inference (2023) · cites this paper as Bzdok et al., 2017
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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 · see citing works
The Elements of Statistical Learning
Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162 · see citing works
Machine learning: Trends, perspectives, and prospects
Jordan, M. I., & Mitchell, T. M. (2015) · Science · doi:10.1126/science.aaa8415 · Cited by 9,955 · see citing works
Lever, J., Krzywinski, M. I., & Altman, N. (2017) · Nature Methods · doi:10.1038/nmeth.4346 · Cited by 1,468 · see citing works
Self-citationModel selection and overfitting
Lever, J., Krzywinski, M. I., & Altman, N. (2016) · Nature Methods · doi:10.1038/nmeth.3968 · Cited by 727 · see citing works
Self-citationEnsemble methods: bagging and random forests
Altman, N., & Krzywinski, M. I. (2017) · Nature Methods · doi:10.1038/nmeth.4438 · Cited by 330 · see citing works
Self-citationAltman, N., & Krzywinski, M. I. (2017) · Nature Methods · doi:10.1038/nmeth.4299 · Cited by 190 · see citing works
Self-citationSampling distributions and the bootstrap
Kulesa, A. B., Krzywinski, M. I., Blainey, P. C., & Altman, N. (2015) · Nature Methods · doi:10.1038/nmeth.3414 · Cited by 156 · see citing works
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Research works printed but not linked: 3
- [5]Hastie T Tibshirani R Friedman J Springer Series in Statistics Heidelberg 2001
- [6]James G Witten D Hastie T Tibshirani R Springer 2013
- [7]Shalev-Shwartz S Ben-David S Cambridge University Press 2014
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Statistics versus machine learning
Bzdok, D., Altman, N., & Krzywinski, M. (2018) · Nature Methods · doi:10.1038/nmeth.4642 · Cited by 1,508 · see citing works
Self-citationSantamaría-García, H., Baez, S., Aponte-Canencio, D. M., Pasciarello, G. O., Donnelly-Kehoe, P. A., Maggiotti, G., Matallana, D., Hesse, E., Neely, A., Zapata, J. G., et al. (2021) · Patterns · doi:10.1016/j.patter.2020.100176 · Cited by 18 · see citing works
Gonzalez-Gomez, R., Ibañez, A., & Moguilner, S. (2023) · Network Neuroscience · doi:10.1162/netn_a_00285 · Cited by 10 · see citing works
Jiwani, Z., Goldberg, S. B., Stroud, J., Young, J., Curtin, J., Dunne, J. D., Simonsson, O., Webb, C. A., Carhart-Harris, R., & Schlosser, M. (2025) · PLOS ONE · doi:10.1371/journal.pone.0310160 · Cited by 6 · see citing works
- Authors
- Bzdok, D., Krzywinski, M., & Altman, N.
- Affiliations
- Institut national de recherche en sciences et technologies du numérique (FR)
- Canada's Michael Smith Genome Sciences Centre (CA)
- Pennsylvania State University (US)
- Venue
- Nature Methods
- Published
- 2017-12
- Volume
- 14
- Issue
- 12
- Pages
- 1119-1120
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- PMC
- PMC5905345
- OpenAlex
- W2772747611
- Cited by
- 246
- References
- 8
- Citations by year
- 2026: 25 · 2025: 44 · 2024: 50 · 2023: 32 · 2022: 35 · 2021: 23 · 2020: 11 · 2019: 13 · 2018: 10 · 2017: 3
- FWCI
- 6.04
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Nature Methods (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- HAL (submittedVersion, other-oa)
- Funders
- National Institute of Mental Health (R01MH074457)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and Algorithms
- Physical Sciences › Computer Science › Information Systems › Data Mining and Machine Learning Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Applications
- Keywords
- machine learning, pattern extraction, data-driven inference, supervised learning, unsupervised learning
- MeSH terms
- Machine Learning, Algorithms, Hormones, Humans, Models, Biological, Sensitivity and Specificity
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