Model card
Random Forest.
scikit-learnopen-sourceRandom Forest
Ensemble of decision trees with random feature subsampling. Classic strong baseline.
§ 01 · Benchmarks
Every benchmark Random Forest has a recorded score for.
| # | Benchmark | Area · Task | Metric | Value | Rank | Date | Source |
|---|---|---|---|---|---|---|---|
| 01 | OpenML-CC18 | Time Series · Tabular Classification | accuracy | 85.7% | #5 | 2025-06-01 | source ↗ |
| 02 | ABIDE I | Medical · Disease Classification | accuracy | 63.0% | #24 | — | source ↗ |
Rank column shows this model’s position vs all other models scored on the same benchmark + metric (competitors after the slash). #1 in red means current SOTA. Sorted by rank, then newest result.
§ 02 · Strengths by area
Where Random Forest actually performs.
§ 03 · Papers
1 paper with results for Random Forest.
- 2025-06-01· 1 result
ConTextTab: A Semantics-Aware Tabular In-Context Learner
Marco Spinaci
§ 05 · Sources & freshness
Where these numbers come from.
ConTextTab Table 1
1
result
research-paper
1
result
1 of 2 rows marked verified.