Abstract
In India the climatic parameters vary too rapidly. In such situation the rain prediction is very challenging. The classification and regression problem pertaining to rainfall can be effectively solved using some efficient machine learning technique. This thought has been a motivation in developing this research article. The secondary data with two attributes viz. humidity and maximum temperature has been used to train binary classification models to cluster it into 2 classes viz. 'Heavy rainfall' & 'Light rainfall'. To develop classification models, two different algorithms viz. K-means, and FCM (Fuzzy C-means) clustering are used in MATLAB, and their performance is compared.
Sign-in/Register to access full text options 
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 callDisclaimer: 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.
