Machine Learning Approaches for Evaluating Statistical Information in the Agr...

Machine Learning Approaches for Evaluating Statistical Information in the Agricultural Sector, Paperback by Martinho, Vitor Joao Pereira Domingues, ISBN 3031546075, ISBN-13 9783031546075, Like New Used, Free shipping in the US

This book presents machine learning approaches to identify the most important predictors of crucial variables for dealing with the challenges of managing production units and designing agriculture policies. Th focuses on the agricultural sector in the European Union and considers statistical information from the Farm Accountancy Data Network (FADN).

Presently, statistical databases present a lot of information for many indicators and, in these contexts, one of the main tasks is to identify the most important predictors of certain indicators. In this way, th presents approaches to identifying the most relevant variables that best support the design of adjusted farming policies and management plans. These subjects are currently important for students, public institutions and farmers. To achieve these objectives, th considers the IBM SPSS Modeler procedures as well as the respective models suggested by this software.

Th is read by students in production engineering, economics and agricultural studies, public bodies and managers in the farming sector.