Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
LEARNING FROM GEOSPATIAL DATA
Problems and important concepts of machine learning
Machine learning algorithms for geospatial data
Contents of the book. Software description
Short review of the literature
EXPLORATORY SPATIAL DATA ANALYSIS. PRESENTATION OF DATA AND CASE STUDIES
Exploratory spatial data analysis
Data pre-processing
Spatial correlations: Variography
Presentation of data
k-Nearest neighbours algorithm: a benchmark model for regression and classification
Conclusions to chapter 2
GEOSTATISTICS
Spatial predictions
Geostatistical conditional simulations
Spatial classification
Software
Conclusions
ARTIFICIAL NEURAL NETWORKS
Introduction
Radial basis function neural networks
General regression neural networks
Probabilistic neural networks
Self-organising maps
Gaussian mixture models and mixture density network
Conclusions
SUPPORT VECTOR MACHINES AND KERNEL METHODS
Introduction to statistical learning theory
Support vector classification
Spatial data classification with SVM
Support vector regression
Advanced topics in kernel methods
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Spese di spedizione:
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In U.S.A.
Descrizione libro Hardcover. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!. Codice articolo S_338920577
Descrizione libro Condizione: Good. Good condition. This is the average used book, that has all pages or leaves present, but may include writing. Book may be ex-library with stamps and stickers. Codice articolo 353-0849382378-gdd