Support Vector Machine based Binary Classification of Humidity

This research work is based on the physical parameter humidity. The value of this parameter is strongly associated with the presence of water vapors in the air. The humidity value above a particular limit results in severe harmful consequences. There exists a huge work already done by various researchers on humidity measurement. However, the present work attempts to classify the data samples having values of maximum temperature & rainfall into 2 classes- Class 1 (Non-hazardous humidity) and Class 2 (hazardous humidity). The classification models have been developed using SVM (Support Vector Machine) technique in MATLAB. The secondary data of humidity has been used to train the models.