chefboost

Decision tree library

A Python library providing a lightweight framework for building decision trees with categorical feature support

A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4.5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting, Random Forest and Adaboost w/categorical features support for Python

GitHub

460 stars
18 watching
101 forks
Language: Python
last commit: 23 days ago
Linked from 1 awesome list

adaboostc45-treescartcategorical-featuresdata-miningdata-sciencedecision-treesgbdtgbmgbrtgradient-boostinggradient-boosting-machinegradient-boosting-machinesid3kagglemachine-learningpythonrandom-forestregression-tree

Backlinks from these awesome lists:

Related projects:

Repository Description Stars
bensadeghi/decisiontree.jl A Julia package implementing popular machine learning algorithms 8
greenfish77/gaenari A C++ library implementing incremental decision tree learning with support for concept drift and online learning to improve model accuracy over time. 25
doubleplusplus/incremental_decision_tree-cart-random_forest An implementation of incremental decision tree algorithms and ensemble methods for efficient machine learning on streaming data 100
florentavellaneda/inferdt This C++ project provides an implementation of decision tree algorithms for classification tasks 7
igrigorik/decisiontree An implementation of the ID3 algorithm for building decision trees 1,439
aia-uclouvain/pydl8.5 An algorithm for inferring optimal binary decision trees in C++ and wrapped by a Python interface 61
stanfordmlgroup/ngboost A Python library implementing a machine learning boosting framework with probabilistic prediction capabilities 1,654
sgrodriguez/ddt A Go-based decision tree library allowing custom rule-based decision making 37
xiyanghu/osdt A Python implementation of an algorithm for constructing decision trees with regularization and various bounding functions to accelerate the search process. 100
gugarosa/opfython An implementation of an optimum-path forest classifier using Python 34
zdanielsresearch/hellingertreesmatlab Implementation of Hellinger Distance Decision Trees and Forests for binary decision problems with imbalanced data and numeric attributes. 1
harshakokel/kigb An open-source software framework that integrates human advice into gradient boosting decision trees for improved performance in machine learning tasks. 8
ryanbressler/cloudforest A high-performance ensemble learning framework for decision trees in Go. 739
johnstonskj/rml-decisiontrees An implementation of decision trees for classification in Racket machine learning. 4
tensorflow/decision-forests Provides tools and APIs for training, serving, and interpreting decision forest models in TensorFlow. 660