Dirk Husmeier – författare
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5 produkter
Neural Networks for Conditional Probability Estimation
Forecasting Beyond Point Predictions
E-bok, 2012
734 kr
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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 …
Probabilistic Modeling in Bioinformatics and Medical Informatics
Av Stephen Roberts, Richard Dybowski m. fl.
E-bok, 2006
2111 kr
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Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following …
Probabilistic Modeling in Bioinformatics and Medical Informatics
Av Dirk Husmeier, Richard Dybowski m. fl.
Häftad, 2010
1690 kr
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Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following …
Neural Networks for Conditional Probability Estimation
Forecasting Beyond Point Predictions
Häftad, 1999
552 kr
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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 …
Probabilistic Modeling in Bioinformatics and Medical Informatics
Av Dirk Husmeier, Richard Dybowski m. fl.
Inbunden, 2005
1641 kr
Lägg i varukorg
Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following …
