Hallo! Tracked shipping to Netherlands with Delivery Duty Paid for just €7 

Ship to
Netherlands
0

My Account

  • argentina
  • chile
  • colombia
  • españa
  • méxico
  • perú
  • estados unidos
  • internacional

menu

Select your country

Americas

Europe

Rest of the world

portada Multivariate Statistical Machine Learning Methods for Genomic Prediction
Type
Physical Book
Author
Publisher
Language
English
Pages
691
Format
Hardcover
Dimensions
23.4 x 15.6 x 3.8 cm
Weight
1.17 kg.
ISBN13
9783030890094
Categories

Multivariate Statistical Machine Learning Methods for Genomic Prediction

Osval Antonio Montesinos López (Author) · Abelardo Montesinos López (Author) · José Crossa (Author) · Springer · Hardcover

Multivariate Statistical Machine Learning Methods for Genomic Prediction - Montesinos López, Osval Antonio ; Montesinos López, Abelardo ; Crossa, José

Cheaper New Book Imported to Netherlands
Delivery: 02 Sep - 07 Sep Shipping: 12 to 14 business days.
€ 56,88
Faster New Book Imported to Netherlands
Delivery: 20 Aug - 24 Aug Shipping: 4 to 5 business days.
€ 69,13
Import costs and 9% BTW included in the price ✅
€ 56,88

Choose the list to add your product or create one New List

Go to My Wishlists
Calculate shipping cost

Synopsis "Multivariate Statistical Machine Learning Methods for Genomic Prediction "

Preface.- Chapter 1.- General elements of genomic selection and statistical learning.- Chapter. 2.- Preprocessing tools for data preparation.- Chapter. 3.- Elements for building supervised statistical machine learning models.- Chapter. 4.- Overfitting, model tuning and evaluation of prediction performance.- Chapter. 5.- Linear Mixed Models.- Chapter. 6.- Bayesian Genomic Linear Regression.- Chapter. 7.- Bayesian and classical prediction models for categorical and count data.- Chapter. 8.- Reproducing Kernel Hilbert Spaces Regression and Classification Methods.- Chapter. 9.- Support vector machines and support vector regression.- Chapter. 10.- Fundamentals of artificial neural networks and deep learning.- Chapter. 11.- Artificial neural networks and deep learning for genomic prediction of continuous outcomes.- Chapter. 12.- Artificial neural networks and deep learning for genomic prediction of binary, ordinal and mixed outcomes.- Chapter. 13.- Convolutional neural networks.- Chapter. 14.- Functional regression.- Chapter. 15.- Random forest for genomic prediction.

Customers reviews

More customer reviews
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)

Frequently Asked Questions about the Book

Is the book original?

All books in our catalog are Original.

In what language is the book written?

The book is written in English.

What is the format of this book?

The binding of this edition is Hardcover.

Questions and Answers about the Book

Do you have a question about the book? Login to be able to add your own question.

Opinions about Bookdelivery

More customer reviews