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..
On the Equivalence of Linear Discriminant Analysis and Least Squares
Authors: Kibok Lee, Junmo Kim
AAAI 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results demonstrate the equivalence of the LDA solution and the proposed LS solution. |
| Researcher Affiliation | Collaboration | Kibok Lee1,2 and Junmo Kim1 1Department of Electrical Engineering, KAIST, Daejeon, Korea 2Samsung Electronics DMC R&D Center, Suwon, Korea |
| Pseudocode | Yes | Algorithm 1 Fast approximation of regularized uncorrelated LDA (RULDA) (p = c 1) 1. Compute YB = ZBL, where ZB = {z Bij} in (5). 2. Solve W = argmin W XT CW YT B 2 F + γ W 2 F . 3. return W |
| Open Source Code | No | No. The paper does not provide any explicit statements about releasing source code or links to a code repository for the described methodology. |
| Open Datasets | Yes | We used three data sets for our experiment: the extended Yale Face Database B (Georghiades, Belhumeur, and Kriegman 2001), the MNIST database of handwritten digits (Le Cun and Cortes 1998), and Isolet (Bache and Lichman 2013). |
| Dataset Splits | No | No. The paper provides the number of training and test samples but does not specify a clear split methodology (e.g., percentages, random seed, k-fold cross-validation) or mention a validation set. |
| Hardware Specification | Yes | All experiments were done in MATLAB on a PC with an Intel Core i73610QM CPU at 2.30 GHz and with 8 GB RAM. |
| Software Dependencies | No | No. The paper mentions using 'MATLAB' but does not provide a specific version number for MATLAB or any other software libraries or tools used in the experiments. |
| Experiment Setup | Yes | The regularization parameter is set to be 10 4 on extended Yale B and 1 on the others. |