This volume includes coverage of statistical, machine learning, and neural network techniques for classification.
The basis for the exploitation of these and related algorithms has been expanded through the integration of contributions to give an objective assessment of the potential for machine learning algorithms in solving key commercial and industrial problems.
As a result of the stat log Project, which was supported by the EU's Esprit Program, this volume was written. The project had the desired outcome of encouraging collaboration amongst workers from many disciplines, which was long overdue in this industry, in addition to the experimental results. A rapidly expanding area of interest is the intersection and interaction between machine learning and statistics. The primary area of shared research is classification, however, communication has been hampered by the use of different terminologies.
Statisticians, AI workers in machine learning, and experts in neural networks have combined in this volume to form new patterns of interaction and collaboration. For those working in medicine, agriculture, industry, finance, and other Applied Studies, we offer this book as a source of useful information. We also hope that it will encourage other scientific communities to form similar partnerships and advance work on the intersection of machine learning and statistics.
