Improving Private Random Forest Prediction Using Matrix Representation
Authors: Arisa Tajima, Joie Wu, Amir Houmansadr
AAAI 2025 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experimental results show significant accuracy improvements of up to 40% compared to state-of-the-art methods. We validate our methods on real-world datasets, demonstrating a significant accuracy improvement of up to 40% compared to existing approaches. |
| Researcher Affiliation | Academia | 1University of Massachusetts Amherst 2Independent Researcher EMAIL, EMAIL, EMAIL |
| Pseudocode | Yes | Algorithm 1: DP M-RF Training Algorithm 2: DP M-RF Prediction Algorithm 3: DP M-RF Framework |
| Open Source Code | Yes | Our code and technical appendix will be available at: https://github.com/ arisa77/mrf-public.git. |
| Open Datasets | Yes | Datasets. We use six popular classification datasets from the UCI ML Repository (Kelly, Longjohn, and Nottingham 2023) with feature dimensions ranging from 4 to 128: Car, Iris, Scale, Adult, Heart, and Mushroom. |
| Dataset Splits | Yes | Unless explicitly denoted, each dataset is split into train and test subsets with a 80:20 ratio. |
| Hardware Specification | Yes | All implementations are in Python and experiments were conducted on a Mac Book Air (M2 chip with 16GB RAM). |
| Software Dependencies | No | The paper mentions 'Python' as the implementation language and 'scikit-learn' for a baseline classifier, but does not provide specific version numbers for these software components. For example: 'All implementations are in Python' and 'the Extra-Trees classifier from scikit-learn'. |
| Experiment Setup | Yes | Figure 2: Test accuracy of different private prediction techniques on various datasets, varying values of privacy loss ϵ with fixed parameters:h = 4, τ = 128 for Car, h = 2, τ = 64 for Iris, h = 2, τ = 128 for Balance, h = 2, τ = 128, q = 2, d = 4 for Heart, h = 3, τ = 125, q = 5, d = 4 for Mushroom and h = 8, τ = 100, q = 4, d = 10 for Adult. |