SML-Bench
http://aksw.org/Projects/SMLBench an entity of type: AlumniProject
| The ultimate goal of SML-Bench is to foster research in machine learning from structured data as well as increase the reproducibility and comparability of algorithms in that area. This is important, since a) the preparation of machine learning tasks in that area involves a significant amount of work and b) there are hardly any cross comparisions across languages as this requires data conversion processes. xsd:string |
| A Benchmark for Symbolic Supervised Machine Learning from Expressive Structured Data xsd:string |
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| 1 xsd:integer |
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| sml-bench xsd:string |
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| projects:DLLearner ↪ DL-Learner projects:ORE ↪ ORE |
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| SML-Bench (Structured Machine Learning Benchmark) is a benchmark for machine learning from structured data. It provides datasets, which contain structured knowledge (beyond plain feature vectors) in languages such as the Web Ontology Language (OWL) or the logic programming language Prolog. For those datasets, SML-Bench defines a number of machine learning tasks, e.g. the prediction of diseases. sysont:Markdown |
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| <https://github.com/SmartDataAnalytics/SML-Bench> | |
| <https://github.com/SmartDataAnalytics/SML-Bench/issues> | |
| <https://github.com/SmartDataAnalytics/SML-Bench> | |
| people:JensLehmann ↪ Prof. Dr. Jens Lehmann |
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| Java xsd:string Prolog xsd:string |
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| aksw:AlumniProject ↪ Alumni Project |
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| SML-Bench xsd:string |
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| <http://sml-bench.aksw.org> |
inverse relations
1 resourcesprojects:DLLearner↪ DL-Learner |
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1 resourcespeople:SimonBin↪ Simon Bin |