starling-lab/BoostSRL
BoostSRL: "Boosting for Statistical Relational Learning." A gradient-boosting based approach for learning different types of SRL models.
This tool helps researchers and data scientists analyze complex datasets where entities have relationships with each other, such as social networks or biological pathways. You provide your data in a logical predicate format, like 'father(X,Y)' or 'male(X)', and it generates a model to predict hidden relationships or classify new entities. The output is a set of logical rules, helping users understand patterns within their relational data.
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Use this if you need to build predictive models from data that explicitly describes relationships between items or individuals, not just independent records.
Not ideal if your data is primarily tabular or easily represented in a standard spreadsheet, without intricate, interconnected relationships.
Stars
31
Forks
24
Language
Java
License
GPL-3.0
Category
Last pushed
Sep 11, 2023
Commits (30d)
0
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