Search Results for author: Larisa Soldatova

Found 3 papers, 0 papers with code

ML-Schema: Exposing the Semantics of Machine Learning with Schemas and Ontologies

no code implementations14 Jul 2018 Gustavo Correa Publio, Diego Esteves, Agnieszka Ławrynowicz, Panče Panov, Larisa Soldatova, Tommaso Soru, Joaquin Vanschoren, Hamid Zafar

The ML-Schema, proposed by the W3C Machine Learning Schema Community Group, is a top-level ontology that provides a set of classes, properties, and restrictions for representing and interchanging information on machine learning algorithms, datasets, and experiments.

BIG-bench Machine Learning

Meta-QSAR: a large-scale application of meta-learning to drug design and discovery

no code implementations12 Sep 2017 Ivan Olier, Noureddin Sadawi, G. Richard Bickerton, Joaquin Vanschoren, Crina Grosan, Larisa Soldatova, Ross D. King

We first carried out the most comprehensive ever comparison of machine learning methods for QSAR learning: 18 regression methods, 6 molecular representations, applied to more than 2, 700 QSAR problems.

BIG-bench Machine Learning Meta-Learning +1

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