Relational One-Class Classification: A Non-Parametric Approach
Authors: Tushar Khot, Sriraam Natarajan, Jude Shavlik
AAAI 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | 4 Experiments We evaluate the following different algorithms: [...] We use area under the Precision-Recall curve (AUC-PR) and accuracy to compare our approaches. |
| Researcher Affiliation | Academia | Tushar Khot and Sriraam Natarajan and Jude Shavlik University of Wisconsin-Madison, {tushar,shavlik}@cs.wisc.edu Indiana University, natarasr@indiana.edu |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | Yes | UW-CSE dataset (Richardson and Domingos 2006) is a standard SRL dataset developed at University of Washington. [...] IMDB is another popular SRL dataset (Mihalkova and Mooney 2007) containing information about actors, directors and movies obtained from imdb.com. [...] we use the Heart dataset which is a multivariate data set with 13 attributes. |
| Dataset Splits | Yes | We pick 20%, 40% and 60% of the labeled examples for training and use all the positives for testing. The results for five-fold cross-validation are shown in Table 2 and Table 3. |
| Hardware Specification | No | The paper does not provide specific hardware details (like GPU/CPU models or types) used for running its experiments. |
| Software Dependencies | No | The paper mentions using 'the Stanford NLP toolkit' but does not specify a version. It also mentions 'SVM' and 'TILDE' but without specific library or software version numbers. |
| Experiment Setup | Yes | The parameter λ (set to 0.5 in experiments) ensures that the distance value decreases gradually as the depth increases. [...] For the weight learning step, we use a step length of η = 0.001. |