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Naive Bayes classifier Web Service
SOAPSoaplab ![header=[] body=[SPAIN] cssheader=[boxoverTooltipHeader] cssbody=[boxoverTooltipBody] delay=[200] Es](/images/flags/es.png?1371827396)
Specified Name (from WSDL):
AnalysisServiceService
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aka
naive_bayes_classifier
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Overview

Provider:
Universitat Pompeu Fabra (UPF)
Location:
SPAIN
Submitter / Source:
Marc Poch Riera
(over 12 years ago)
WSDL Location:
http://ws03.iula.upf.edu/soaplab2-axis/services/lexicon_terminology_extraction.naive_bayes_classifier?wsdl (download last cached WSDL file)
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This webservice performs traditional Naive Bayes classification of instances given in a weka file. It outputs the predicted classification for each instance and some statistics about the performance of the classification. The parameters needed as input can be learnt using estimate_bayesian_parameters webservice.
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- ds_lsr_analysis :
- analysis :
- input :
- type : Lexicon_Terminology_Extraction
- name : naive_bayes_classifier
- analysis_extension :
- installation : Soaplab2 default installation
- output :
- description : cat: donat un conjunt de signatures en un fitxer weka (test_file.arff), classificar-les usant el fitxer de pesos per cada pista (theta_file.csv).
es: dado un conjunto de signaturas en un fichero weka (test_file.arff), classificarlas usando el fichero de pesos para cada pista (theta_file.csv).
en: given a set of signatures in a weka file (test_file.arff), classify them using the parameters estimated for each cue (theta_file.csv).
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This Web Service is free for research use. It was developed in the framework of the PANACEA project, funded by the European Union Language Technologies Area, Information and Communication Technologies, of the 7th Framework Programme (7FP-ITC-248064).
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These Terms and Conditions of Service will apply to your use of this web-service and by using the web-service, you are agreeing to these Terms and Conditions of Service.
(a) Authorized Users: users affiliated with a research or non-profit educational institution.
(b) Authorized Use: Restricted to use for research or educational purposes. You should have the right to legally use the “Input data” to the web service and hence acquire all rights to the output data.
(c) Prohibited use: commercial purposes, including charging a fee-for-service; it is also prohibited to use input data for which you did not obtain the necessary rights.
(d) Warranty; Disclaimers: authorized Users recognize that IULA is an aggregator of third-party web services. This web-service owner warrants that to its knowledge use of the web service in accordance with the terms of this document will not infringe the copyright of any third party.
(e) Liability: The web service and IULA will not be liable, and Users agree that they will not hold IULA or the web service liable for any loss, injury, claim, liability, damages, costs, and/or attorneys fees of any kind that result from the use of this web service.
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@inproceedings{padro_web_2012,
address = {Stroudsburg ({USA)}},
title = {Web Services for Bayesian Learning},
volume = {29-31},
url = {http://hdl.handle.net/10230/20329},
booktitle = {{EACL} 2012: Workshop on Computational Models of Language Acquisition and Loss: Proceedings of the Conference; 2012 April 24; Avignon, France},
publisher = {Association for Computational Linguistics ({ACL)}},
author = {Padró, Muntsa and Bel, Núria},
year = {2012}
}
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SOAP Operations (23)
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