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DTSTAMP:20260615T214832Z
UID:3899160d-3d93-444d-922e-a16c1c41ddf1
DTSTART:20170911T070000Z
DTEND:20170913T150000Z
DESCRIPTION:This course aims to introduce the core principles and biomedica
 l applications of different data mining and machine learning techniques in
  a hands-on manner. It will tackle both unsupervised (clustering\, frequen
 t pattern mining\, data projection) and supervised (classification) techni
 ques. The methods that will be seen include hierarchical clustering\, k- m
 eans clustering\, item set mining\, association rule mining\, principle co
 mponent analysis\, support vector machines\, random forests\, bayesian net
 works and artificial neural networks. Attendees will be introduced to the 
 basic operations of these data mining techniques\, with a focus on the pra
 ctical use and interpretation of these procedures rather than the mathemat
 ical formulas. In addition\, attendants will be introduced to some importa
 nt data processing and performance evaluation methods related to these dat
 a mining techniques. The software used in this course will be R. The cours
 e itself will consist of 50% theory lessons\, 40% hands-on practicals and 
 10% application case studies.\n\nOrganised by biomina:\n\nDr. Pieter Meysm
 an\nProf. dr. Kris Laukens\n
LOCATION:Antwerpen Groenenborgerlaan
SUMMARY:Biomolecular data mining: a hands-on training
URL;VALUE=URI:http://www.biomina.be/BioMolDM2017
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