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Neural Nets for Conditional Probability Estimation
Dirk Husmeier
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Description for Neural Nets for Conditional Probability Estimation
Paperback. Using two alternative approaches, the GM network and the GM-RVFL model, this study of the applications of neural networks includes a case study of the prediction of housing prices in the Boston metropolitan area, and examines the required modifications to standard approaches. Series: Perspectives in Neural Computing. Num Pages: 298 pages, 13 black & white illustrations. BIC Classification: JFFR; UYQN. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 16. Weight in Grams: 460.
Conventional applications of neural networks usually predict a single value as a function of given inputs. In forecasting, for example, a standard objective is to predict the future value of some entity of interest on the basis of a time series of past measurements or observations. Typical training schemes aim to minimise the sum of squared deviations between predicted and actual values (the 'targets'), by which, ideally, the network learns the conditional mean of the target given the input. If the underlying conditional distribution is Gaus sian or at least unimodal, this may be a satisfactory approach. However, for a ... Read more
Conventional applications of neural networks usually predict a single value as a function of given inputs. In forecasting, for example, a standard objective is to predict the future value of some entity of interest on the basis of a time series of past measurements or observations. Typical training schemes aim to minimise the sum of squared deviations between predicted and actual values (the 'targets'), by which, ideally, the network learns the conditional mean of the target given the input. If the underlying conditional distribution is Gaus sian or at least unimodal, this may be a satisfactory approach. However, for a ... Read more
Product Details
Format
Paperback
Publication date
1999
Publisher
Springer London Ltd United Kingdom
Number of pages
298
Condition
New
Series
Perspectives in Neural Computing
Number of Pages
275
Place of Publication
England, United Kingdom
ISBN
9781852330958
SKU
V9781852330958
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
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