Evaluating supervised machine learning algorithms to predict recreational fishing success : A multiple species, multiple algorithms approach
This report examines three different machine learning algorithms and their effectiveness for predicting recreational fishing success. Recreational fishing is a huge pastime but reliable methods of predicting fishing success have largely been missing. This report compares random forest, linear regres...
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| Format: | Others |
| Language: | English |
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KTH, Skolan för datavetenskap och kommunikation (CSC)
2015
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-172995 |