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Predicting Climate Variability over the Indian Region Using Data Mining Strategies

In this paper an approach based on expectation maximization (EM) clustering to find the climate regions and a support vector machine to build a predictive model for each of these regions is proposed. To minimize the biases in the estimations a ten cross fold validation is adopted both for obtaining clusters and building the predictive models. The EM clustering could identify all the zones as per the Koppen classification over Indian region. The proposed strategy when employed for predicting temperature has resulted in an RMSE of $1.19$ in the Montane climate region and $0.89$ in the Humid Sub Tropical region as compared to $2.9$ and $0.95$ respectively predicted using k-means and linear regression method.

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