gaenari 
 Decision Tree Library
 A C++ library implementing incremental decision tree learning with support for concept drift and online learning to improve model accuracy over time.
c++ incremental decision tree
26 stars
 3 watching
 2 forks
 
Language: C++ 
last commit: over 3 years ago   aic45-decision-treeconcept-driftcpp-librarycpp17-librarycsv-parserdataframe-librarydecision-tree-classifiergnuplot-cppincremental-learningj48json-parsermachine-learningonline-learningsqlite-driver 
 Related projects:
| Repository | Description | Stars | 
|---|---|---|
|    |  An implementation of incremental decision tree algorithms and ensemble methods for efficient machine learning on streaming data | 100 | 
|    |  An implementation of the ID3 algorithm for building decision trees | 1,438 | 
|    |  A Python library providing a lightweight framework for building decision trees with categorical feature support | 463 | 
|    |  A Go-based decision tree library allowing custom rule-based decision making | 37 | 
|    |  A Julia package implementing popular machine learning algorithms | 8 | 
|    |  An implementation of decision trees for classification in Racket machine learning. | 4 | 
|    |  An algorithm for inferring optimal binary decision trees in C++ and wrapped by a Python interface | 62 | 
|    |  This C++ project provides an implementation of decision tree algorithms for classification tasks | 7 | 
|    |  An implementation of a binary decision tree using ActionScript 3.0 for AI bot/agent in video games. | 3 | 
|    |  Develops decision trees from derivatives of ReLU networks to improve model interpretability and robustness | 21 | 
|    |  An open-source system that enables secure and private machine learning predictions using decision tree models. | 25 | 
|    |  A Node.js implementation of a decision tree using the ID3 algorithm for classification | 210 | 
|    |  Provides tools and APIs for training, serving, and interpreting decision forest models in TensorFlow. | 666 | 
|    |  A high-performance ensemble learning framework for decision trees in Go. | 740 | 
|    |  Enables storage and exchange of decision tree models in a format independent of specific frameworks or platforms. | 742 |