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A Comparison of Alternative Tests of Significance for the Problem of $m$ Rankings
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“As for comparing the classifiers over multiple datasets, we followed the recommendations in Demˇ sar (2006) and used the Friedman test (Friedman, 1940) to reject the null hypothesis.”
From Deep learning for time series classification: a review (2019) · cites this paper as Friedman, 1940
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Convex ensemble learning with sparsity and diversity
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Hybrid biogeography-based evolutionary algorithms
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“The Friedman test (Friedman 1940) was used to detect whether or not significant differences generally exist in the multiple comparisons.”
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Profit optimizing customer churn prediction with Bayesian network classifiers
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“We reject the null hypothesis of the Friedman test that there are no significant differences between the approaches on the CVBUG data (p − value < 0.001). The post-hoc Nemenyi test found that our Herbold2020-FTA has the best best mean ranking, but the diffference is not significant in comparison to Kallis2019-FT and P…”
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“For H1 (reliance), we assess the results with the Friedman test [22, 23], analyzing user uncertainty values (low and high) separately to find significant differences in the factors’ distributions.”
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“, non-parametric tests like the Friedman test [21]with post-hocNemenyi test [22] as proposed byDem sar [23].”
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“One of the most common non-parametric tests is the well-known Friedman test [114].”
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Qiao, Y., Wu, N., He, Y., Li, Z., & Chen, T. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.118068 · Cited by 41
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“Firstly, we perform the Friedman test, which is a non-parametric statistical test that checks whether the difference between two treatments is due to chance or not [20].”
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Ensembles for multi-target regression with random output selections
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“The Friedman test (Friedman 1940), with the correction by Iman and Davenport (1980), is used to determine statistical significance.”
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An improved elephant herding optimization for global optimization problems
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“The numbers of teeth are integers and vary in a range of [12, 60].”
BackgroundMethodManzella, F., Pagliarini, G., Sciavicco, G., & Stan, I. E. (2023) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2022.102486 · Cited by 47
“…to evaluate which of the sample types (cough, breath, or cough + breath) is most suited for this kind of prediction, and whether multi-frame learning is statistically more effective than standard learning, the accuracy results for the different versions can be compared using the Friedman test [91].”
Analysis of clustering methods for crop type mapping using satellite imagery
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“Alongside the MCB test, we consider a non-parametric Friedman test [30, 31] for determining the robustness of our experimental evaluation.”
MethodExperimental Comparison of Methods for Multi-label Classification in different Application Domains
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“To validate the proposed approach, a statistical test named ‘Friedman-Test’ [44] is applied at the 5% significance level.”
MethodNag, K., & Pal, N. R. (2019) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2019.2927526 · Cited by 40
“At first, we perform Friedman test [79], [80] to check if there exists significant differences among the performances (measured in terms of accuracy) of the comparing 35 (one proposed and 34 existing) methods.”
MethodBiomedical data analysis using neuro-fuzzy model with post-feature reduction
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Label distribution learning: A local collaborative mechanism
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A data-driven missing value imputation approach for longitudinal datasets
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“First, we performed the Friedman’s test, a rank-based non-parametric version of ANOVA with repeated measures (Friedman, 1940).”
MethodClassification of crisis-related data on Twitter using a deep learning-based framework
Paul, N. R., Sahoo, D., & Balabantaray, R. C. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-12183-w · Cited by 41
Chandra, T. B., Singh, B. K., & Jain, D. (2022) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2022.106947 · Cited by 39
Noise-Tolerant Discrimination Indexes for Fuzzy γ Covering and Feature Subset Selection
Huang, Z., & Li, J. (2022) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3175922 · Cited by 39
“Moreover, Friedman test [53] and Nemenyi test [54] are employed to analyze the statistical differences among the compared algorithms in terms of classification accuracy.”
MethodKalman filter-based method for Online Sequential Extreme Learning Machine for regression problems
Nobrega, J. P., & Oliveira, A. L. I. (2015) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2015.05.010 · Cited by 39
Metadata
- Authors
- Friedman, M.
- Corresponding author
- Friedman, Milton
- Venue
- The Annals of Mathematical Statistics
- Publisher
- Institute of Mathematical Statistics
- Published
- 1940-03
- Volume
- 11
- Issue
- 1
- Pages
- 86-92
- ISSN
- 0003-4851 (ISSN-L)
- OpenAlex
- W2016944307
- Cited by
- 2,785
- References
- 4
- Citations by year
- 2026: 191 · 2025: 256 · 2024: 244 · 2023: 253 · 2022: 264 · 2021: 231 · 2020: 209 · 2019: 173 · 2018: 133 · 2017: 106 · 2016: 132 · 2015: 93 · 2014: 82 · 2013: 72 · 2012: 67
- FWCI
- 5.07
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The Annals of Mathematical Statistics (publishedVersion)
- Project Euclid (Cornell University) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Distribution Estimation and Applications
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Game Theory and Voting Systems
- Keywords
- tests of significance, rank tests, comparison of statistical tests
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.
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