Machine Learning by Adaptive Local Hyperplane Algorithm: Theory and Applications - Vojislav Kecman - Books - VDM Verlag Dr. Müller - 9783639261844 - May 16, 2010
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Machine Learning by Adaptive Local Hyperplane Algorithm: Theory and Applications


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Machine learning algorithms play a key role in many fields of science, technology and business. Classification and regression are two fundamental tasks in machine learning. This book is devoted to develop learning algorithms for solving the classification and regression problems. A novel learning algorithm dubbed as adaptive local hyperplane (ALH) is introduced to solve the general classification and regression problems. The ALH algorithm belongs to the nonparametric paradigm and it is an extension of the K-local hyperplane distance nearest neighbor (HKNN) algorithm. The ALH algorithm and its extensions have been successfully applied into many real world tasks such as face recognition and DNA microarray analysis and protein sequence function prediction.

Media Books     Paperback Book   (Book with soft cover and glued back)
Released May 16, 2010
ISBN13 9783639261844
Publishers VDM Verlag Dr. Müller
Pages 144
Dimensions 225 × 8 × 150 mm   ·   222 g
Language English  

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