Designing Early Warning System

Zusatztext

Currency crisis is a never ending episode in the economics story. Some questions like how to prevent this crisis had been answered a long time ago. But how accurate the prediction can be? In this book, we introduce an application of machine learning in modeling an early warning system to predict currency crisis with the aim of increasing the prediction accuracy. Also, this book introduces WEKA software which is a collection of machine learning algorithms for data mining.

Autorenportrait

Nor Azuana Ramli is a PhD student from Malaysia. She received a BSc degree in mathematical industry from Universiti Teknologi Malaysia in 2008. Her research involves the application of machine learning system in modeling Early Warning System to predict currency crisis. This is her first book which is also a part of her ongoing research.

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