Deutsch
Deutschland
Anmelden
Tipp von eurobuch.de
Ähnliche Bücher
Weitere, andere Bücher, die diesem Buch sehr ähnlich sein könnten:
Buch verkaufen
Anbieter, die das Buch mit der ISBN 9783639288681 ankaufen:
Suchtools
Buchtipps
Aktuelles
Werbung
FILTER
- 0 Ergebnisse
Kleinster Preis: 54,85 €, größter Preis: 69,20 €, Mittelwert: 59,97 €
DIMENSIONALITY REDUCTION FOR CLASSIFICATION WITH HIGH-DIMENSIONAL DATA
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)
DIMENSIONALITY REDUCTION FOR CLASSIFICATION WITH HIGH-DIMENSIONAL DATA - neues Buch

ISBN: 9783639288681

ID: 9783639288681

High-dimensional data refers to data with a large number of variables. Classifying these data is a difficult problem because the enormous number of variables poses challenges to conventional classification methods and renders many classical techniques impractical. A natural solution is to add a dimensionality reduction step before a classification technique is applied. We Propose three methods to deal with this problem: a simulated annealing (SA) based method, a multivariate adaptive High-dimensional data refers to data with a large number of variables. Classifying these data is a difficult problem because the enormous number of variables poses challenges to conventional classification methods and renders many classical techniques impractical. A natural solution is to add a dimensionality reduction step before a classification technique is applied. We Propose three methods to deal with this problem: a simulated annealing (SA) based method, a multivariate adaptive stochastic search (MASS) method, and a functional adaptive classification (FAC) method. The third method considers functional predictors. They all utilize stochastic search algorithms to select a handful of optimal transformation directions from a large number of random directions in each iteration. These methods are designed to mimic variable selection type methods, such as the Lasso, or variable combination methods, such as PCA, or a method that combines the two approaches. We demonstrate the strengths of our methods on an extensive range of simulation and real-world studies. Textbooks New, Books~~Mathematics~~Probability & Statistics~~General, DIMENSIONALITY-REDUCTION-FOR-CLASSIFICATION-WITH-HIGH-DIMENSIONAL-DATA~~Siva-Tian, , , , , , , , , , VDM Verlag Dr. Mueller Akt.ges.&Co.KG

Neues Buch Barnesandnoble.com
MPN: , SKU 9783639288681 Versandkosten:zzgl. Versandkosten
Details...
(*) Derzeit vergriffen bedeutet, dass dieser Titel momentan auf keiner der angeschlossenen Plattform verfügbar ist.
Dimensionality Reduction For Classification with High-Dimensional Data - Siva Tian
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)
Siva Tian:
Dimensionality Reduction For Classification with High-Dimensional Data - neues Buch

ISBN: 9783639288681

ID: 38988dd9bdc2ed105ad777fbb329b1dd

Dimensionality Reduction For Classification with High-Dimensional Data High-dimensional data refers to data with a large number of variables. Classifying these data is a difficult problem because the enormous number of variables poses challenges to conventional classification methods and renders many classical techniques impractical. A natural solution is to add a dimensionality reduction step before a classification technique is applied. We Propose three methods to deal with this problem: a simulated annealing (SA) based method, a multivariate adaptive stochastic search (MASS) method, and a functional adaptive classification (FAC) method. The third method considers functional predictors. They all utilize stochastic search algorithms to select a handful of optimal transformation directions from a large number of random directions in each iteration. These methods are designed to mimic variable selection type methods, such as the Lasso, or variable combination methods, such as PCA, or a method that combines the two approaches. We demonstrate the strengths of our methods on an extensive range of simulation and real-world studies. Bücher / Fremdsprachige Bücher / Englische Bücher 978-3-639-28868-1, VDM Verlag

Neues Buch Buch.de
Nr. 23810368 Versandkosten:Bücher und alle Bestellungen die ein Buch enthalten sind versandkostenfrei, sonstige Bestellungen innerhalb Deutschland EUR 3,-, ab EUR 20,- kostenlos, Bürobedarf EUR 4,50, kostenlos ab EUR 45,-, Sofort lieferbar, zzgl. Versandkosten
Details...
(*) Derzeit vergriffen bedeutet, dass dieser Titel momentan auf keiner der angeschlossenen Plattform verfügbar ist.
DIMENSIONALITY REDUCTION FOR CLASSIFICATION WITH HIGH-DIMENSIONAL DATA - Siva Tian
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)
Siva Tian:
DIMENSIONALITY REDUCTION FOR CLASSIFICATION WITH HIGH-DIMENSIONAL DATA - neues Buch

ISBN: 9783639288681

ID: 94fc4019c62aa4d4a6941e8cf35a8ca0

High-dimensional data refers to data with a large number of variables. Classifying these data is a difficult problem because the enormous number of variables poses challenges to conventional classification methods and renders many classical techniques impractical. A natural solution is to add a dimensionality reduction step before a classification technique is applied. We Propose three methods to deal with this problem: a simulated annealing (SA) based method, a multivariate adaptive stochastic search (MASS) method, and a functional adaptive classification (FAC) method. The third method considers functional predictors. They all utilize stochastic search algorithms to select a handful of optimal transformation directions from a large number of random directions in each iteration. These methods are designed to mimic variable selection type methods, such as the Lasso, or variable combination methods, such as PCA, or a method that combines the two approaches. We demonstrate the strengths of our methods on an extensive range of simulation and real-world studies. Bücher / Naturwissenschaften, Medizin, Informatik & Technik / Mathematik / Stochastik & Statistik, [PU: VDM Verlag Dr. Müller, Saarbrücken]

Neues Buch Dodax.de
Nr. 57a0b4662c9bc808f72c4670 Versandkosten:Versandkosten: 0.0 EUR, Lieferzeit: 7 Tage, DE. (EUR 0.00)
Details...
(*) Derzeit vergriffen bedeutet, dass dieser Titel momentan auf keiner der angeschlossenen Plattform verfügbar ist.
DIMENSIONALITY REDUCTION FOR CLASSIFICATION WITH HIGH-DIMENSIONAL DATA - Siva Tian
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)
Siva Tian:
DIMENSIONALITY REDUCTION FOR CLASSIFICATION WITH HIGH-DIMENSIONAL DATA - Taschenbuch

2010, ISBN: 3639288688

ID: 9612496327

[EAN: 9783639288681], Neubuch, [PU: Vdm Verlag Aug 2010], This item is printed on demand - Print on Demand Titel. - High-dimensional data refers to data with a large number of variables. Classifying these data is a difficult problem because the enormous number of variables poses challenges to conventional classification methods and renders many classical techniques impractical. A natural solution is to add a dimensionality reduction step before a classification technique is applied. We Propose three methods to deal with this problem: a simulated annealing (SA) based method, a multivariate adaptive stochastic search (MASS) method, and a functional adaptive classification (FAC) method. The third method considers functional predictors. They all utilize stochastic search algorithms to select a handful of optimal transformation directions from a large number of random directions in each iteration. These methods are designed to mimic variable selection type methods, such as the Lasso, or variable combination methods, such as PCA, or a method that combines the two approaches. We demonstrate the strengths of our methods on an extensive range of simulation and real-world studies. 124 pp. Englisch

Neues Buch Abebooks.de
AHA-BUCH GmbH, Einbeck, Germany [51283250] [Rating: 5 (von 5)]
NEW BOOK Versandkosten:Versandkostenfrei (EUR 0.00)
Details...
(*) Derzeit vergriffen bedeutet, dass dieser Titel momentan auf keiner der angeschlossenen Plattform verfügbar ist.
Dimensionality Reduction for Classification with High-Dimensional Data - Siva Tian
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)
Siva Tian:
Dimensionality Reduction for Classification with High-Dimensional Data - Taschenbuch

ISBN: 9783639288681

Paperback, [PU: VDM Verlag], Probability & Statistics

Neues Buch Bookdepository.com
Versandkosten:Versandkostenfrei (EUR 0.00)
Details...
(*) Derzeit vergriffen bedeutet, dass dieser Titel momentan auf keiner der angeschlossenen Plattform verfügbar ist.

Details zum Buch
DIMENSIONALITY REDUCTION FOR CLASSIFICATION WITH HIGH-DIMENSIONAL DATA

High-dimensional data refers to data with a large number of variables. Classifying these data is a difficult problem because the enormous number of variables poses challenges to conventional classification methods and renders many classical techniques impractical. A natural solution is to add a dimensionality reduction step before a classification technique is applied. We Propose three methods to deal with this problem: a simulated annealing (SA) based method, a multivariate adaptive stochastic search (MASS) method, and a functional adaptive classification (FAC) method. The third method considers functional predictors. They all utilize stochastic search algorithms to select a handful of optimal transformation directions from a large number of random directions in each iteration. These methods are designed to mimic variable selection type methods, such as the Lasso, or variable combination methods, such as PCA, or a method that combines the two approaches. We demonstrate the strengths of our methods on an extensive range of simulation and real-world studies.

Detailangaben zum Buch - DIMENSIONALITY REDUCTION FOR CLASSIFICATION WITH HIGH-DIMENSIONAL DATA


EAN (ISBN-13): 9783639288681
ISBN (ISBN-10): 3639288688
Taschenbuch
Erscheinungsjahr: 2010
Herausgeber: VDM Verlag Dr. Müller

Buch in der Datenbank seit 07.12.2009 03:44:47
Buch zuletzt gefunden am 06.07.2017 17:42:51
ISBN/EAN: 9783639288681

ISBN - alternative Schreibweisen:
3-639-28868-8, 978-3-639-28868-1


< zum Archiv...
Benachbarte Bücher