ODT-with-noisy-outcomes
by sjia1
NeuIPS2019: Optimal Decision Tree with noisy outcomes
AI summary
Decision Tree Algorithm
An implementation of an optimal decision tree algorithm with noisy outcomes, specifically tailored to simulate real-world decision-making under uncertainty
- stars
- 0
- forks
- 1
- watching
- 1
- awesome list
- 1
Similar projects
Found by comparing what the projects do, not just their names.
Decision Tree Accelerator
A Python implementation of an algorithm for constructing decision trees with regularization and various bounding functions to accelerate the search process.
Decision Tree Algorithm
This C++ project provides an implementation of decision tree algorithms for classification tasks
Decision tree learner
An algorithm for inferring optimal binary decision trees in C++ and wrapped by a Python interface
Decision Tree Library
An implementation of incremental decision tree algorithms and ensemble methods for efficient machine learning on streaming data
Decision Tree Algorithm
An R implementation of Hellinger distance decision tree algorithm.
Machine learning library
A Julia package implementing popular machine learning algorithms
Decision Tree
An implementation of a binary decision tree using ActionScript 3.0 for AI bot/agent in video games.
Decision tree library
A Python library providing a lightweight framework for building decision trees with categorical feature support
Gradient Boosting Algorithm
An implementation of Gradient Boosted Decision Trees with sparse output for high-dimensional data
Decision Tree Library
A Go-based decision tree library allowing custom rule-based decision making
Robust decision trees
An implementation of robust decision tree based models against adversarial examples using the XGBoost framework.
Decision tree library
An implementation of the ID3 algorithm for building decision trees
Decision Tree Classifier
A Java implementation of a fairness-aware decision tree classifier for online stream-based classification
Label weighting algorithm
An implementation of a method to improve classification accuracy on noisy labels by reweighting their importance
Decision tree predictor
An open-source system that enables secure and private machine learning predictions using decision tree models.
Featured in 1 awesome list
Each link jumps to the spot where the list mentions ODT-with-noisy-outcomes.
