Decision Forest C++ library with a scikit-learn compatible Python interface
Project description
koho (TM)
koho (Hawaiian word for ‘to estimate’) is a Decision Forest C++ library with a scikit-learn compatible Python interface.
Python implementation with Criterion implemented in Cython!
Classification
Numerical (dense) data
Class balancing
Multi-Class
Single-Output
Build order: depth first
Impurity criteria: gini
n Decision Trees with soft voting
Split a. features: best over k (incl. all) random features
Split b. thresholds: 1 random or all thresholds
Stop criteria: max depth, (pure, no improvement)
Bagging (Bootstrap AGGregatING) with out-of-bag estimates
Important Features
Export Graph
Copyright 2019, AI Werkstatt (TM). All rights reserved.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.