Bankruptcy Prediction through Soft Computing based Deep Learning Technique

Highlights the latest research on deep learning integrated with hierarchical Bayesian statistics for bankruptcy prediction.

Presents the mathematical framework of the prediction model in a very lucid manner.

Experiments use real-world datasets and the results support the theoretical hypothesis.

A valuable resource for postgraduate students and researchers in deep learning and mathematical finance.

The proposed prediction model can be applied to any skewed real life dataset.

Autorentext

Arindam Chaudhuri: Arindam Chaudhuri is currently a Data Scientist at the Samsung R & D Institute Delhi, India. He has worked in industry, research and teaching in the field of machine learning domain for the past 16 years. His current research interests include pattern recognition, machine learning, soft computing, optimization and big data. He received his MTech and PhD in Computer Science from Jadavpur University, Kolkata, India and Netaji Subhas University, Kolkata, India in 2005 and 2011 respectively. He has published 2 research monographs and over 40 articles in international journals and conference proceedings. He has served as a reviewer for several international journals and conferences. Soumya K Ghosh: Soumya K Ghosh is currently a Professor at the Department of Computer Science Engineering at the Indian Institute of Technology Kharagpur, India. His current research interests include pattern recognition, machine learning, soft computing, cloud applications and sensornetworks. He received his MTech and PhD in Computer Science Engineering from the Indian Institute of Technology Kharagpur, India in 1996 and 2002 respectively. He has over 25 years of experience in industry, research and teaching. He has published 2 research monographs and over 100 articles in international journals and conference proceedings. He has served as a reviewer for several international journals and conferences.

Inhalt

Introduction.- Need of this Research.- Literature Review.- Bankruptcy Prediction Methodology.- Need for Risk Classification.- Experimental Framework: Bankruptcy Prediction using Soft Computing based Deep Learning Technique.- Datasets Used.- Experimental Results.- Conclusion