Modern Data Mining Algorithms in C++ and CUDA C

Idioma: inglés

Editorial: Apress, Apress Jun 2020, 2020

1484259874 / 9781484259870

  • Tapa blanda
  • Nuevo
Ver todos los detalles

Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

Vendedor de 5 estrellas

Vendedor de AbeBooks desde 23 de enero de 2017

Ver los artículos de este vendedor
Tapa blanda

Condición: Nuevo

EUR 69,54

Envío por EUR 60,00 
Se envía de Alemania a Estados Unidos de America

Cantidad disponible: 1 disponibles

Añadir al carrito
Devoluciones gratuitas de 30 días

Descripción del artículo del vendedor

This item is printed on demand - Print on Demand Titel. Neuware -Discover a variety of data-mining algorithms that are useful for selecting small sets of important features from among unwieldy masses of candidates, or extracting useful features from measured variables.As a serious data miner you will often be faced with thousands of candidate features for your prediction or classification application, with most of the features being of little or no value. You'll know that many of these features may be useful only in combination with certain other features while being practically worthless alone or in combination with most others. Some features may have enormous predictive power, but only within a small, specialized area of the feature space. The problems that plague modern data miners are endless. This book helps you solve this problem by presenting modern feature selection techniques and the code to implement them. Some of these techniques are:Forward selection component analysisLocal feature selectionLinking features and a target with a hidden Markov modelImprovements on traditional stepwise selectionNominal-to-ordinal conversionAll algorithms are intuitively justified and supported by the relevant equations and explanatory material. The author also presents and explains complete, highly commented source code.The example code is in C++ and CUDA C but Python or other code can be substituted; the algorithm is important, not the code that's used to write it.What You Will LearnCombine principal component analysis with forward and backward stepwise selection to identify a compact subset of a large collection of variables that captures the maximum possible variation within the entire set.Identify features that may have predictive power over only a small subset of the feature domain. Such features can be profitably used by modern predictive models but may be missed by other feature selection methods.Find an underlying hidden Markov model that controls the distributions of feature variables and the target simultaneously. The memory inherent in this method is especially valuable in high-noise applications such as prediction of financial markets.Improve traditional stepwise selection in three ways: examine a collection of 'best-so-far' feature sets; test candidate features for inclusion with cross validation to automatically and effectively limit model complexity; and at each step estimate the probability that our results so far could be just the product of random good luck. We also estimate the probability that the improvement obtained by adding a new variable could have been just good luck. Take a potentially valuable nominal variable (a category or class membership) that is unsuitable for input to a prediction model, and assign to each category a sensible numeric value that can be used as a model input.Who This Book Is ForIntermediate to advanced data science programmers and analysts.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 240 pp. Englisch.

N° de ref. del artículo 9781484259870

Título
Modern Data Mining Algorithms in C++ and CUDA C
Autor
Timothy Masters
Editorial
Apress, Apress Jun 2020
Año de publicación
2020
Estado
Neu
Encuadernación
Taschenbuch
Idioma
inglés
ISBN 10
1484259874
ISBN 13
9781484259870
Peso del artículo
460 gramos
Dimensiones
254x178x14 mm

buchversandmimpf2000

Emtmannsberg, BAYE, Alemania

Vendedor de 5 estrellas

Vendedor de AbeBooks desde 23 de enero de 2017

Tarifas de envío de Alemania a Estados Unidos de America

ArtículoDe 60 a 60 días hábilesDe 60 a 60 días hábiles
Primer artículoEUR 60,00EUR 75,00
Los plazos de entrega los establecen los vendedores y varían según el transportista y la ubicación. Los pedidos que pasan por la aduana pueden sufrir retrasos y los compradores son responsables de los aranceles o tarifas asociadas. Los vendedores pueden ponerse en contacto con usted en relación con cargos adicionales para cubrir cualquier aumento en los costes de envío de los artículos.

Métodos de pago

  • Visa
  • Mastercard
  • American Express
  • Carte Bleue
  • Apple Pay
  • Google Pay
  • Cheque
  • PayPal

Descripción de la tienda

Impressum Thorsten Retsch Buchversand Mimpf2000 Oberölschnitz 16 95517 Emtmannsberg Deutschland Telefon: 09209-2023188 Email: mimpf2000@online.de USt-ID-Nr.: DE 235096871 Wir führen gebrauchte Bücher aus allen Sparten der Literatur

Especialidad

Modernes Antiquariat - Bücher von 1960 bis heute

Información empresarial del vendedor

buchversandmimpf2000

Alemania