Multi-Class Support Vector Machine with Maximizing Minimum Margin
Authors: Feiping Nie, Zhezheng Hao, Rong Wang
AAAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Empirical evaluations demonstrate the effectiveness and superiority of our proposed method over existing multi-classification methods. |
| Researcher Affiliation | Academia | Feiping Nie1,2*, Zhezheng Hao1,2, Rong Wang2 1School of Cybersecurity, Northwestern Polytechnical University, Xi an, China 2 School of Artificial Intelligence, Optics and Electronics (i OPEN), Northwestern Polytechnical University, Xi an, China |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | Yes | Code is available at https://github.com/zz-haooo/M3SVM. |
| Open Datasets | Yes | The datasets chosen for evaluation include Cornell, ISOLET, HHAR, USPS, ORL, Dermatology, Vehicle and Glass, which represent diverse data types (including image, speech, document, etc). They can all be found at 2. https://archive.ics.uci.edu/ml/datasets.php. |
| Dataset Splits | No | The paper mentions training and testing but does not provide specific information about validation dataset splits (e.g., percentages, sample counts, or explicit mention of a validation set). |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., exact GPU/CPU models, processor types, or memory amounts) used for running its experiments. |
| Software Dependencies | No | The paper mentions software components like 'Adam optimization strategy' but does not provide specific version numbers for any software dependencies or libraries. |
| Experiment Setup | Yes | For the hyperparameters involved in M3SVM, λ is set to ten equidistant values within the interval [1 10 4, 1 10 1], while p is set on a grid of [1, 2, ..., 8]. For all comparative methods, we adhere to the authors default parameter settings and, where necessary, similarly conduct parameter grid searches to achieve fair comparisons as far as possible. |