Weather forecasting has been one of the most scientifically and technologically challenging problems around the world in the last century. One of the most popular methods used for weather prediction is data mining. Over the years many data mining techniques have been used to forecast weather such as Decision tree and Artificial neural network. In this paper we present a new technique for weather prediction namely CPT+ which is highly efficient than all the methods used till date for prediction.


Here we present a novel prediction model for weather prediction which losslessly compresses the training data so that all relevant information is available for each prediction. Our approach is incremental, offers a low time complexity for its training phase and is easily adaptable for different applications and contexts.