Hybrid Classifier: Methods Of Data, Knowledge, And Classifier Combination (studies In Computational Intelligence)
by Michal Wozniak /
2013 / English / PDF
3.2 MB Download
This book delivers a definite and compact knowledge on how
hybridization can help improving the quality of computer
classification systems. In order to make readers clearly realize
the knowledge of hybridization, this book primarily focuses on
introducing the different levels of hybridization and
illuminating what problems we will face with as dealing with such
projects. In the first instance the data and knowledge
incorporated in hybridization were the action points, and then a
still growing up area of classifier systems known as combined
classifiers was considered. This book comprises the
aforementioned state-of-the-art topics and the latest research
results of the author and his team from Department of Systems and
Computer Networks, Wroclaw University of Technology, including as
classifier based on feature space splitting, one-class
classification, imbalance data, and data stream classification.
This book delivers a definite and compact knowledge on how
hybridization can help improving the quality of computer
classification systems. In order to make readers clearly realize
the knowledge of hybridization, this book primarily focuses on
introducing the different levels of hybridization and
illuminating what problems we will face with as dealing with such
projects. In the first instance the data and knowledge
incorporated in hybridization were the action points, and then a
still growing up area of classifier systems known as combined
classifiers was considered. This book comprises the
aforementioned state-of-the-art topics and the latest research
results of the author and his team from Department of Systems and
Computer Networks, Wroclaw University of Technology, including as
classifier based on feature space splitting, one-class
classification, imbalance data, and data stream classification.
