HUGIML interactive demos
Explore HUGIML through interactive benchmark, causal-analysis, and governance dashboards, guided browser-playable video demonstrations, and chat-first LLM model-review examples.
Benchmark Analysis Dashboard
100-dataset evaluation, with 50 real-world and 50 synthetic datasets, covering predictive quality, timing, robustness, RPTE behavior, and inspection complexity.
OpenML-CC18OpenML-CC18 Benchmark Dashboard
50 completed tasks from the 72-task catalog, evaluated on official outer splits with nested model selection and matched ensemble comparisons.
TabZillaTabZilla Benchmark Dashboard
Rotating train, validation, and test evaluation on 31 matched datasets with predictive, timing, RPTE, and complexity analysis.
PMLBmini Benchmark Dashboard
All 44 binary-classification datasets evaluated with repeated rotating folds and matched model comparisons.
TabArenaTabArena Official Leaderboard
Official-reference Elo and detailed metric analysis with overall, binary, multiclass, default, tuned, and combined views.
ScalabilityScalability Dashboard
Measured fit-time and inference-latency scaling against XGBoost and LightGBM across row, feature, and mining-budget sweeps.
Causal Investigation Studio Demo
Interactive preview of shared-vocabulary T-HUG treatment-effect analysis: potential outcomes, repeated cross-fitting, DR/AIPW estimates, overlap sensitivity, interpretable causal regions, and matched T-learner comparisons.
Governance Studio Demo
Static preview of the Dash-based Governance Studio: validation evidence, representation audit, HUG pattern inventory, case-level explanations, representation pruning, data quality review, and monitoring signals.
HUGIML Guided Video Demonstrations
Short guided walkthroughs covering the HUGIML overview, data-scientist workflow, data-to-decision modeling, interpretability, stakeholder communication, and governance. Videos play directly in the browser with no local setup required.
LLM Chat Workbench
Chat-style workbench mock covering dataset profiling, feature importance, pattern breakdown, model pruning, rebuild comparison, and governance artifact preparation.
LLM exampleLending Credit-Risk Assistant
Chat-style walkthrough for building, tuning, scoring, and explaining an interpretable lending model — covering risk drivers, pattern summaries, and governance preparation for credit committee review.
LLM exampleCard Default Assistant
Chat-style collections workflow for profiling cardholder risk, comparing rule sets, explaining high-risk accounts, and trimming the model representation for hand-off.