Prediction Accuracy of Financial Data - Applying Several Resampling Techniques
Ali, Mohammad Reza
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With the help of Data Mining and Machine Learning, prediction has been a very popular and demanding instrument to plan and accomplish a future goal. The financial sector is one of the crucial sectors of present human society. Predicting the correct outcome is a pivotal matter in this sector. In this work, an assessment was done to the prediction efficiency by applying several Machine Learning Classification Algorithms and resampling methods. These techniques were applied to financial data, more specifically to Bank Marketing in order to predict the tendency of clients to subscribe to a bank term deposit. For the correct prediction of the outcome, imbalance in the data set affects the results greatly. Consequently, the prediction becomes inaccurate. Researchers are working this issue and many investigators are using different methods. This research paper uses some sampling techniques together with several conventional Machine Learning algorithms to improve the prediction precision.