Skip to main content

A garden of scikit-learn compatible trees, and I had few modifications to it.

Project description

# Scikit-Garden

Forked from https://github.com/scikit-garden/scikit-garden

Scikit-Garden or skgarden (pronounced as skarden) is a garden for Scikit-Learn compatible decision trees and forests.

## Installation

Scikit-Garden depends on NumPy, SciPy, Scikit-Learn and Cython. So make sure these dependencies are installed using pip:

`` pip3 install setuptools numpy scipy scikit-learn cython # or pip3 install -r requirements.txt ``

After that my Scikit-Garden fork can be installed using pip.

`` pip install git+https://git@github.com/Demangio/scikit-garden.git ``

## Available models

### Regressors

  • ExtraTreesRegressor (with return_std support)

  • ExtraTreesQuantileRegressor

  • RandomForestRegressor (with return_std support)

  • RandomForestQuantileRegressor

## Usage

The estimators in Scikit-Garden are Scikit-Learn compatible and can serve as a drop-in replacement for Scikit-Learn’s trees and forests.

`` from sklearn.datasets import load_boston X, y = load_boston()

### Use QuantileForests for quantile estimation from skgarden import RandomForestQuantileRegressor rfqr = RandomForestQuantileRegressor(random_state=0) rfqr.fit(X, y) y_mean = rfqr.predict(X) y_median = rfqr.predict(X, 50) ``

## What changes in this release

Change default predict method to the same as QuantReg package. This version is faster and include parametric estimation. Adaptation of code to higher versions of dependencies.

## Important links - API Reference: https://scikit-garden.github.io/api/ - Examples: https://scikit-garden.github.io/examples/ - Modifications source: https://stackoverflow.com/questions/51483951/quantile-random-forests-from-scikit-garden-very-slow-at-making-predictions

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

scikit-garden-forked-0.0.7.tar.gz (13.1 kB view details)

Uploaded Source

File details

Details for the file scikit-garden-forked-0.0.7.tar.gz.

File metadata

  • Download URL: scikit-garden-forked-0.0.7.tar.gz
  • Upload date:
  • Size: 13.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.22.0 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.8.10

File hashes

Hashes for scikit-garden-forked-0.0.7.tar.gz
Algorithm Hash digest
SHA256 819a22734243860a6d77fc800f6c6dd4b0afa9a5df1602c2676fa99ed39707cb
MD5 580ca7fdf525aaf214e8d4383fd70406
BLAKE2b-256 b13b1e4d0899f9397037e7f2b108f09c5776e0d145f312b8cbf7d27b569f8eaf

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page