The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
How Many Trees in a Random Forest?
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Citations
Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
The WEKA data mining software: an update
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., & Witten, I. H. (2009) · ACM SIGKDD Explorations Newsletter · doi:10.1145/1656274.1656278 · Cited by 17,750
Breiman, L. (1996) · Machine Learning · doi:10.1007/bf00058655 · Cited by 16,325
A Comparison of Alternative Tests of Significance for the Problem of $m$ Rankings
Friedman, M. (1940) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177731944 · Cited by 2,785
Measuring the VC-Dimension of a Learning Machine
Vapnik, V., Levin, E., & Cun, Y. L. (1994) · Neural Computation · doi:10.1162/neco.1994.6.5.851 · Cited by 388 · cited 1×
“, its cardinality) or its capacity provided by the VC dimension [30].”
Background
Cited by
A survey on semi-supervised learning
van Engelen, J. E., & Hoos, H. H. (2020) · Machine Learning · doi:10.1007/s10994-019-05855-6 · Cited by 2,666
Improved Random Forest for Classification
Paul, A., Mukherjee, D. P., Das, P., Gangopadhyay, A., Chintha, A. R., & Kundu, S. (2018) · IEEE Transactions on Image Processing · doi:10.1109/tip.2018.2834830 · Cited by 483
Orengo, H. A., Conesa, F. C., Garcia-Molsosa, A., Lobo, A., Green, A. S., Madella, M., & Petrie, C. A. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2005583117 · Cited by 165
House Price Prediction Using Machine Learning and Neural Networks
Varma, A., Sarma, A., Doshi, S., & Nair, R. (2018) · 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT) · doi:10.1109/icicct.2018.8473231 · Cited by 157
Soe, Y. N., Feng, Y., Santosa, P. I., Hartanto, R., & Sakurai, K. (2020) · Electronics · doi:10.3390/electronics9010144 · Cited by 110
DeepCPI: A Deep Learning-Based Framework for Large-Scale in Silico Drug Screening
Wan, F., Zhu, Y., Hu, H., Dai, A., Cai, X., Chen, L., Gong, H., Xia, T., Yang, D., Wang, M.-W., et al. (2019) · Genomics, Proteomics & Bioinformatics · doi:10.1016/j.gpb.2019.04.003 · Cited by 92
Islam, M. S., Islam, M. T., Sarker, S., Jame, H. A., Nishat, S. S., Jani, M. R., Rauf, A., Ahsan, S., Shorowordi, K. M., Efstathiadis, H., et al. (2022) · ACS Omega · doi:10.1021/acsomega.2c01076 · Cited by 76
Metadata
- Authors
- Oshiro, T. M., Perez, P. S., & Baranauskas, J. A.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2012
- Pages
- 154-168
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1797580880
- Cited by
- 912
- References
- 6
- FWCI
- 6.65
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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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.
