koho (TM)
koho (Hawaiian word for ‘to estimate’) is a Decision Forest C++ library with a scikit-learn compatible Python interface.
Classification
Numerical (dense) data
Missing values (Not Missing At Random (NMAR))
Class balancing
Multi-Class
Multi-Output (single model)
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
Change Log: 1.1.0 Multi-Output (single model) 1.0.0 Missing Values (NMAR) : Python, Cython(bindings), C++ 0.0.2 Criterion implemented in Cython 0.0.1 Classification : Python only
Copyright 2019, AI Werkstatt (TM). All rights reserved.
1 maintainer
Metadata
1 maintainer
Release files for koho 1.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| koho-1.1.0.tar.gz | 159.1 kB | Details |
Release files / koho-1.1.0.tar.gz
| Download URL | koho-1.1.0.tar.gz |
|---|---|
| Size | 159.1 kB |
| Tags | Source |
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twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.3
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