@prefix ocrer: <http://purl.org/net/OCRe/research.owl#> .
@prefix owl:   <http://www.w3.org/2002/07/owl#> .
@prefix scires: <http://vivoweb.org/ontology/scientific-research#> .
@prefix xsd:   <http://www.w3.org/2001/XMLSchema#> .
@prefix skos:  <http://www.w3.org/2004/02/skos/core#> .
@prefix rdfs:  <http://www.w3.org/2000/01/rdf-schema#> .
@prefix ocresd: <http://purl.org/net/OCRe/study_design.owl#> .
@prefix swo:   <http://www.ebi.ac.uk/efo/swo/> .
@prefix cito:  <http://purl.org/spar/cito/> .
@prefix geo:   <http://aims.fao.org/aos/geopolitical.owl#> .
@prefix ocresst: <http://purl.org/net/OCRe/statistics.owl#> .
@prefix dcterms: <http://purl.org/dc/terms/> .
@prefix vivo:  <http://vivoweb.org/ontology/core#> .
@prefix event: <http://purl.org/NET/c4dm/event.owl#> .
@prefix vann:  <http://purl.org/vocab/vann/> .
@prefix foaf:  <http://xmlns.com/foaf/0.1/> .
@prefix c4o:   <http://purl.org/spar/c4o/> .
@prefix fabio: <http://purl.org/spar/fabio/> .
@prefix vcard: <http://www.w3.org/2006/vcard/ns#> .
@prefix thkoeln: <http://cris.nrw/hisinone#> .
@prefix vitro: <http://vitro.mannlib.cornell.edu/ns/vitro/0.7#> .
@prefix vitro-public: <http://vitro.mannlib.cornell.edu/ns/vitro/public#> .
@prefix rdf:   <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix ocresp: <http://purl.org/net/OCRe/study_protocol.owl#> .
@prefix bibo:  <http://purl.org/ontology/bibo/> .
@prefix obo:   <http://purl.obolibrary.org/obo/> .
@prefix ro:    <http://purl.obolibrary.org/obo/ro.owl#> .

obo:BFO_0000031  a  owl:Class ;
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                <https://fis.th-koeln.de/vivo/individual/publ_11840> .

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thkoeln:Journalartikel
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        a                         thkoeln:Journalartikel , obo:IAO_0000030 , owl:Thing , obo:BFO_0000001 , thkoeln:Publikation , foaf:Document , thkoeln:Artikel , bibo:Document , obo:BFO_0000031 , obo:BFO_0000002 ;
        rdfs:label                "Simplifying Hyperparameter Tuning in Online Machine Learning" , "RDF description of Simplifying Hyperparameter Tuning in Online Machine Learning - https://fis.th-koeln.de/vivo/individual/publ_11840" ;
        thkoeln:URL               "https://arxiv.org/abs/2402.11594" ;
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        thkoeln:sprache           "englisch" ;
        thkoeln:status            "validiert" ;
        thkoeln:subtitle          "The spotRiverGUI" ;
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                <https://fis.th-koeln.de/vivo/individual/FF_001> ;
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        bibo:abstract             "Batch Machine Learning (BML) reaches its limits when dealing with very large amounts of streaming data. This is especially true for available memory, handling drift in data streams, and processing new, unknown data. Online Machine Learning (OML) is an alternative to BML that overcomes the limitations of BML. OML is able to process data in a sequential manner, which is especially useful for data streams. The `river` package is a Python OML-library, which provides a variety of online learning algorithms for classification, regression, clustering, anomaly detection, and more. The `spotRiver` package provides a framework for hyperparameter tuning of OML models. The `spotRiverGUI` is a graphical user interface for the `spotRiver` package. The `spotRiverGUI` releases the user from the burden of manually searching for the optimal hyperparameter setting. After the data is provided, users can compare different OML algorithms from the powerful `river` package in a convenient way and tune the selected algorithms very ef" ;
        bibo:doi                  "10.48550/arXiv.2402.11594" ;
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        vivo:freetextKeyword      "Streaming Data" , "Online Machine Learning" , "Machine Learning (cs.LG)" , "Sequential Parameter Optimization" , "FOS: Computer and information sciences" , "Artificial Intelligence (cs.AI)" , "River" , "Hyperparameter Tuning" ;
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        rdfs:label                "De.arXiv.org" ;
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