I-ROCKET: Interpretable ROCKET
Year: 2026
Type: software
Abstract: 0.2.0 (2026-03-18) Feature stability selection: Added get_stable_features() as a robust alternative to RFE for identifying important features across CV folds. Class-mean visualization functions: Added plot_class_mean_activation() (side-by-side activation and convolution output), plot_multi_kernel_summary() (heatmap across classes), and plot_aggregate_activation() (importance-weighted sum with differential). Aggregate temporal occlusion: Added aggregate_temporal_occlusion() for computing occlusion sensitivity over all trials grouped by class. RF diagram font size: Increased y-axis label font size from 5.5 to 8 for readability. Public kneedle: Renamed _kneedle to kneedle (public API). CI fix: Corrected tests.yml to use pip install -e . (removed nonexistent [viz] extra). pyproject.toml: Added three_bumps to py-modules. Demonstration notebooks for Receptive Field Mapping (demo_RF_mapping.ipynb) and the Breiman waveform dataset (demo_waveform.ipynb) and two benchmark scripts (benchmark_waveform.py and benchmark_ucr.py) were added to the examples directory.
Author: Laubach, Mark
Institution: American University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7136104667