Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Solving M-Modes Using Heuristic Search
Authors: Cong Chen, Changhe Yuan, Chao Chen
IJCAI 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We evaluated our method by comparing to the algorithm by Chen et al. [2014] (called DP) on both synthetic and real datasets. |
| Researcher Affiliation | Academia | Cong Chen, Changhe Yuan, Chao Chen CUNY Graduate Center and CUNY Queens College |
| Pseudocode | Yes | Algorithm 1 provides a pseudo code for this preprocessing step. |
| Open Source Code | No | The paper does not provide any statement or link indicating the availability of open-source code for the described methodology. |
| Open Datasets | Yes | We selected data of different dimensions from UCI repository [Lichman, 2013]. We also used the ADHD-200 dataset [Biswal et al., 2010]. |
| Dataset Splits | No | The paper does not provide specific details on training, validation, or test dataset splits or cross-validation setup. |
| Hardware Specification | No | The paper does not provide specific details about the hardware (e.g., CPU, GPU models, memory) used for running the experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers (e.g., library names, programming languages, or solvers with their versions) that would be needed for replication. |
| Experiment Setup | Yes | For each setting, we generated ten tree models and computed the average running time. The label size L was fixed to be three. This experiment is designed to systematically test the influence of each parameter on the search and DP algorithms. The base setting is d = 60, t = 6, δ = 3, and M = 4. |