On Ranking and Choice Models
Authors: Shivani Agarwal
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | As one example, Figure 2 shows the results obtained by applying our method to sports choice survey data in which 253 respondents each rated 7 sports on a scale of 1 5 based on how much they enjoyed each sport.5 As can be seen, the method accurately discovers two categories corresponding to individual and team sports, and identiļ¬es a third category for jogging; |
| Researcher Affiliation | Academia | Shivani Agarwal Radcliffe Institute for Advanced Study, Harvard University, Cambridge, MA, USA Indian Institute of Science, Bangalore, India shivani@csa.iisc.ernet.in |
| Pseudocode | No | No structured pseudocode or algorithm blocks were found in the paper. |
| Open Source Code | No | The paper does not provide any explicit statement or link indicating that the source code for the described methodologies is publicly available. |
| Open Datasets | No | The paper mentions 'sports choice survey data in which 253 respondents each rated 7 sports' used for an example, but does not provide a specific link, DOI, or formal citation for public access to this dataset. |
| Dataset Splits | No | The paper does not provide specific details on dataset splits (e.g., percentages, sample counts, or citations to predefined splits) for training, validation, or testing. |
| Hardware Specification | No | The paper does not provide specific details about the hardware (e.g., GPU/CPU models, memory) used to run experiments. |
| Software Dependencies | No | The paper does not list specific software dependencies with version numbers that would be needed to replicate the experiment. |
| Experiment Setup | No | The paper does not provide specific experimental setup details such as hyperparameter values, training configurations, or system-level settings. |