MDA-TSK-FS: Ablation Experiment Results for Multi-View Fuzzy System

Zhiqi Huang published ablation experiment results for the MDA-TSK-FS model on May 11, 2026. The data compares the performance of a novel multi-view TSK fuzzy system with deformable Gaussian membership functions and a rule-level attention mechanism against baselines. Results include classification accuracies on five public multi-view datasets: Caltech7 (94.38%), Handwritten (98.62%), Dermatology (98.58%), Forest (88.57%), and EEG (69.75%).

Use Cases

• Benchmarking fuzzy system components based on reported ablation study results
• Analyzing the impact of deformable antecedent structures on model accuracy
• Evaluating rule-level attention mechanisms for multi-view classification tasks
• Comparing model generalization across heterogeneous data sources like EEG and images

Strengths

• Includes specific performance metrics, such as a 9.25% joint improvement in EEG classification accuracy over the baseline
• Results are validated across five distinct public datasets, demonstrating consistency
• The dataset is small (5.5 KB) and available under a permissive CC-BY-4.0 license

Limitations

• Row count and column-level documentation are unknown, limiting suitability assessment
• The dataset is tiny (5.5 KB), indicating it contains summary results rather than raw experimental data
• Description metadata is limited; actual data structure requires manual inspection after download

Provenance

Source

Zhiqi Huang via figshare

Collection Method

Results from ablation experiments on a proposed machine learning model.

Freshness

Last updated 2026-05-11 17:23:01