Supervised machine learning: optimization framework and applications with sas and r
Auteur :
Kolosova, Tanya / Berestizhevsky, Samuel
Éditeur :
Taylor & Francis Ltd
ISBN :
9780367538828
Date de publication :
29 avr. 2022
Dimensions :
23,4 x 15,6 cm
Poids :
340 g
Langue :
Anglais
Pays d'origine :
Grande Bretagne
AI framework intended to solve a problem of bias-variance tradeoff for supervised learning methods in real-life applications. It comprises of bootstrapping to create multiple training and testing data sets, design and analysis of statistical experiments and optimal hyper-parameters for ML methods.