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..
A Gradient-Based Split Criterion for Highly Accurate and Transparent Model Trees
Authors: Klaus Broelemann, Gjergji Kasneci
IJCAI 2019 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In this section, we will evaluate the effectiveness of this novel method on multiple datasets. The experiments cover both classification and regression. |
| Researcher Affiliation | Industry | Klaus Broelemann and Gjergji Kasneci SCHUFA Holding AG, Wiesbaden, Germany |
| Pseudocode | Yes | Algorithm 1 Training Model Trees... Algorithm 2 Gradient-Based Split Finding |
| Open Source Code | No | The paper does not provide an explicit statement or link for open-source code for the described methodology. |
| Open Datasets | Yes | All datasets come from public sources2 [Yeh and Lien, 2009; Zikeba et al., 2016] and cover both classification and regression tasks. The number of samples and attributes of these datasets are displayed in Tab. 3. |
| Dataset Splits | Yes | For our experiments, we performed 4-fold cross validation and averaged the 4 performance measurements. |
| Hardware Specification | No | The paper does not provide specific details about the hardware used for the experiments. |
| Software Dependencies | No | The paper does not specify version numbers for any software dependencies. |
| Experiment Setup | Yes | With transparency and shallow trees in mind, we restrict all model trees to a fixed depth of 1, 2, or 3. ... For our experiments, we performed 4-fold cross validation and averaged the 4 performance measurements. |