Modeling and optimizing callus growth and development in Cannabis sativa using random forest and support vector machine in combination with a genetic algorithm.

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Title: Modeling and optimizing callus growth and development in Cannabis sativa using random forest and support vector machine in combination with a genetic algorithm.
Authors: Hesami, Mohsen1, Jones, Andrew Maxwell Phineas1, amjones@uoguelph.ca
Source: Applied Microbiology & Biotechnology; Jun2021, Vol. 105 Issue 12, p5201-5212, 12p
Database: Applied Science & Technology Source
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  Data: Modeling and optimizing callus growth and development in Cannabis sativa using random forest and support vector machine in combination with a genetic algorithm.
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=151103675
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        Value: 10.1007/s00253-021-11375-y
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      – Code: eng
        Text: English
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        PageCount: 12
        StartPage: 5201
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      – TitleFull: Modeling and optimizing callus growth and development in Cannabis sativa using random forest and support vector machine in combination with a genetic algorithm.
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            – D: 15
              M: 06
              Text: Jun2021
              Type: published
              Y: 2021
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