Papers › RMDL: Random Multimodel Deep Learning for Classification
RMDL: Random Multimodel Deep Learning for Classification
Kamran Kowsari, Mojtaba Heidarysafa, Donald E. Brown, Kiana Jafari Meimandi, Laura E. Barnes
The continually increasing number of complex datasets each year necessitates ever improving machine learning methods for robust and accurate categorization of these data. This paper introduces Random Multimodel Deep Learning (RMDL): a new ensemble, deep learning approach for classification. Deep learning models have achieved state-of-the-art results across many domains. RMDL solves the problem of finding the best deep learning structure and architecture while simultaneously improving robustness and accuracy through ensembles of deep learning architectures. RDML can accept as input a variety data to include text, video, images, and symbolic. This paper describes RMDL and shows test results for image and text data including MNIST, CIFAR-10, WOS, Reuters, IMDB, and 20newsgroup. These test results show that RDML produces consistently better performance than standard methods over a broad range of data types and classification problems.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Hierarchical Text Classification of Blurbs (GermEval 2019) | LOCAL DATASET | RMDL (15 RDLs | Accuracy (%) | 90.79 | #1 of 1 | Archive leaderboard | report |
| Image Classification | CIFAR-10 | RMDL (30 RDLs) | Percentage correct | 91.21 | #194 of 265 | Archive leaderboard | report |
| Image Classification | MNIST | RMDL (30 RDLs) | Accuracy | 99.82 | #5 of 81 | Archive leaderboard | report |
| Image Classification | MNIST | RMDL (30 RDLs) | Percentage error | 0.18 | #5 of 81 | Archive leaderboard | report |
| Text Classification | 20NEWS | RMDL (15 RDLs) | Accuracy | 87.91 | #6 of 16 | Archive leaderboard | report |
| Unsupervised Pre-training | Measles | RMDL | Accuracy (%) | 0.1 | #5 of 5 | Archive leaderboard | report |
| Unsupervised Pre-training | UCI measles | Sensitivity | 89.1 | #1 of 3 | Archive leaderboard | report | |
| Unsupervised Pre-training | UCI measles | RMDL 3 RDLs | Sensitivity | 0.8739 | #2 of 3 | Archive leaderboard | report |
| Unsupervised Pre-training | UCI measles | RMDL (30 RDLs) | Sensitivity (VEB) | 90.69 | #3 of 3 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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