Simple, fast random forests

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Project description

Biosphere

Simple, fast random forests.

Random forests with a runtime of O(n d log(n) + n_estimators d n max_depth) instead of O(n_estimators mtry n log(n) max_depth).

biosphere is available as a rust crate and as a Python package.

Benchmarks

Ran on an M1 Pro with n_jobs=4. Wall-time to fit a Random Forest including OOB score with 400 trees to the NYC Taxi dataset, minimum over 10 runs. After feature engineering, the dataset consists of 5 numerical and 7 one-hot encoded features.

model	1000	2000	4000	8000	16000	32000	64000	128000	256000	512000	1024000	2048000
biosphere	0.04s	0.08s	0.15s	0.32s	0.65s	1.40s	2.97s	6.48s	15.53s	37.91s	96.69s	231.82s
scikit-learn	0.28s	0.34s	0.46s	0.69s	1.23s	2.47s	4.99s	10.49s	22.11s	51.04s	118.95s	271.03s

Project details

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This version

0.3.0

Mar 14, 2022

0.2.2

Feb 22, 2022

0.2.1

Jan 13, 2022

0.2.0

Jan 11, 2022

0.1.0

Dec 30, 2021

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