RobustTrees
Robust decision trees
An implementation of robust decision tree based models against adversarial examples using the XGBoost framework.
[ICML 2019, 20 min long talk] Robust Decision Trees Against Adversarial Examples
67 stars
7 watching
11 forks
Language: C++
last commit: over 2 years ago
Linked from 1 awesome list
adversarial-examplesdecision-treesgbdtgbmgbrtrobust-decision-treesxgboost
benedekrozemberczki/awesome-decision-tree-papersRelated projects:
| Repository | Description | Stars |
|---|---|---|
 chong-z/tree-ensemble-attack | An approach to create adversarial examples for tree-based ensemble models | 22 |
 pzuh/decisiontree | An implementation of a binary decision tree using ActionScript 3.0 for AI bot/agent in video games. | 3 |
 guanghelee/neurips19-certificates-of-robustness | Provides a framework for computing tight certificates of adversarial robustness for randomly smoothed classifiers. | 17 |
 max-andr/provably-robust-boosting | Provides provably robust machine learning models against adversarial attacks | 50 |
 florentavellaneda/inferdt | This C++ project provides an implementation of decision tree algorithms for classification tasks | 7 |
 robustbench/robustbench | A standardized benchmark for measuring the robustness of machine learning models against adversarial attacks | 682 |
 serengil/chefboost | A Python library providing a lightweight framework for building decision trees with categorical feature support | 463 |
 hendrycks/robustness | Evaluates and benchmarks the robustness of deep learning models to various corruptions and perturbations in computer vision tasks. | 1,030 |
 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 |
 kaurao/hddt | An R implementation of Hellinger distance decision tree algorithm. | 10 |
 sjia1/odt-with-noisy-outcomes | An implementation of an optimal decision tree algorithm with noisy outcomes, specifically tailored to simulate real-world decision-making under uncertainty | 0 |
 johnstonskj/rml-decisiontrees | An implementation of decision trees for classification in Racket machine learning. | 4 |
 rgf-team/rgf | A collection of implementations and wrappers for a tree ensemble machine learning method | 379 |
 sgrodriguez/ddt | A Go-based decision tree library allowing custom rule-based decision making | 37 |
 zdanielsresearch/hellingertreesmatlab | Implementation of Hellinger Distance Decision Trees and Forests for binary decision problems with imbalanced data and numeric attributes. | 2 |