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| dc.contributor | Vellido Alcacena, Alfredo |
| dc.contributor | Ribas Ripoll, Vicent |
| dc.contributor.author | Bilal, Ahsan |
| dc.date.accessioned | 2018-07-06T09:18:56Z |
| dc.date.available | 2018-07-06T09:18:56Z |
| dc.date.issued | 2018-04-26 |
| dc.identifier.uri | http://hdl.handle.net/2117/119037 |
| dc.description.abstract | Feature selection is an important technique to find the most relevant features. Apache Spark is a big data processing framework but unable to cope with approx. 0.74 million features in our Obesity dataset. However, we tackle this challenge in 2-phase pipeline. |
| dc.language.iso | eng |
| dc.publisher | Universitat Politècnica de Catalunya |
| dc.subject | Àrees temàtiques de la UPC::Informàtica |
| dc.subject.lcsh | Big data |
| dc.subject.lcsh | Machine learning |
| dc.subject.lcsh | Genomics |
| dc.subject.other | Obesity Prediction |
| dc.subject.other | Feature Selection |
| dc.subject.other | Apache Spark |
| dc.subject.other | Genomic Data |
| dc.subject.other | SNPs |
| dc.title | Big data analytics for obesity prediction |
| dc.title.alternative | Big data analytics in healt |
| dc.type | Master thesis |
| dc.subject.lemac | Dades massives |
| dc.subject.lemac | Aprenentatge automàtic |
| dc.subject.lemac | Genòmica |
| dc.identifier.slug | 131677 |
| dc.rights.access | Open Access |
| dc.date.updated | 2018-04-30T04:01:34Z |
| dc.audience.educationlevel | Màster |
| dc.audience.mediator | Facultat d'Informàtica de Barcelona |
| dc.contributor.covenantee | Fundació Eurecat |
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