Stock image for illustration purposes only - book cover, edition or condition may vary.
Fusion Methods for Unsupervised Learning Ensembles
Bruno Baruque
€ 120.29
FREE Delivery in Ireland
Description for Fusion Methods for Unsupervised Learning Ensembles
Paperback. This book examines the potential of the ensemble meta-algorithm by describing and testing a technique based on the combination of ensembles and statistical PCA that is able to determine the presence of outliers in high-dimensional data sets. Series: Studies in Computational Intelligence. Num Pages: 158 pages, biography. BIC Classification: UYQ. Category: (G) General (US: Trade). Dimension: 235 x 155 x 9. Weight in Grams: 256.
The application of a “committee of experts” or ensemble learning to artificial neural networks that apply unsupervised learning techniques is widely considered to enhance the effectiveness of such networks greatly. This book examines the potential of the ensemble meta-algorithm by describing and testing a technique based on the combination of ensembles and statistical PCA that is able to determine the presence of outliers in high-dimensional data sets and to minimize outlier effects in the final results. Its central contribution concerns an algorithm for the ensemble fusion of topology-preserving maps, referred to as Weighted Voting Superposition (WeVoS), which has been devised ... Read more
The application of a “committee of experts” or ensemble learning to artificial neural networks that apply unsupervised learning techniques is widely considered to enhance the effectiveness of such networks greatly. This book examines the potential of the ensemble meta-algorithm by describing and testing a technique based on the combination of ensembles and statistical PCA that is able to determine the presence of outliers in high-dimensional data sets and to minimize outlier effects in the final results. Its central contribution concerns an algorithm for the ensemble fusion of topology-preserving maps, referred to as Weighted Voting Superposition (WeVoS), which has been devised ... Read more
Product Details
Format
Paperback
Publication date
2014
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Germany
Number of pages
158
Condition
New
Series
Studies in Computational Intelligence
Number of Pages
141
Place of Publication
Berlin, Germany
ISBN
9783642423284
SKU
V9783642423284
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
Reviews for Fusion Methods for Unsupervised Learning Ensembles