Modeling Rainfall Prediction: A Naive Bayes Approach
Rainfall prediction has become a very important part in terms of agriculture and industries. The precise prediction
of rainfall can detect the massive rainfall and may provide warnings and information regarding the disasters. Various
techniques were developed and implemented to predict rainfall, but did not achieve much accuracy due to varying weather
data. In this work we have tried we have implemented Naïve Bayes approach to build rainfall prediction model which will
predict the rainfall with appreciable accuracy. . Historical weather data set of Srinagar, India is gathered from November
2015 to November 2016 is from http://www.wundergrounds.com website. Temperature, Humidity, sea level pressure, wind
speed and Events attributes are selected from 9 available attributes from better results. Experimental results of various
performance measures show that Naïve Bayes approach to predict rainfall has appreciable accuracy and acceptance.
Keywords - Weather Forecasting, Data Mining, Naive Bayes Classifier, Confusion Matrix, Precision.