randomforest
Random Forest classifier implementation in Nim
Summary
| Latest Version | Unknown |
|---|---|
| License | GPL-3.0 |
| CI Status | Failing |
| Stars | 4 |
| Forks | 0 |
| Open Issues | 0 |
| Last Commit | 2021-10-13 |
| Downloads | 0 |
| Last Indexed | 2026-09-06 06:05 |
Tags
Installation
nimble install randomforest
choosenim install randomforest
git clone https://github.com/izikeros/randomforest
OS Compatibility
| Platform | Linux | macOS | Windows | FreeBSD | OpenBSD | NetBSD | Android | iOS | WASM | Embedded |
|---|---|---|---|---|---|---|---|---|---|---|
| randomforest | ✓ | ✓ | ✓ | - | - | - | - | - | - | - |
Source
| Repository | https://github.com/izikeros/randomforest |
|---|---|
| Homepage | https://github.com/izikeros/randomforest |
| Registry Source | github |
README
Random forest classifier
Nim implementation of RandomForestClassifier. The interface is a subset of Python's scikit-learn sklearn.ensemble.RandomForestClassifier
Requirements
nim>=1.0
Installation
nimble install randomforest
Usage
import randomforest
clf = RandomForestClassifier(n_estimators=10, criterion="gini")
clf.fit(X_train, y_train)
y = clf.predict(X_test)
Credits
Thank you Jason Brownlee for the article How to Implement Random Forest From Scratch in Python - this implementation was inspired by approach used in the article.
Related projects
DecisionTreeNim - Nim package for decision trees and random forest scikit-learn - Machine learning library for Python - used as reference implementation.