Abstract
Prediction of agriculture yield with the help of data mining tools and techniques is one of the emerging research domains from past couple of years. This paper focuses on studying the effects of rainfall and relative humidity on three different stages of wheat crop and thus generating rules about crop yield using decision tree induction technique. A comparison of different classification algorithms is also done to discover the best rules about wheat crop yield with maximum accuracy and least errors. These study findings will help the farmers in future to predict their wheat crop yield in advance before crop growing season.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Advanced Research in Computer Science
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
