EAN: 9783031546075

MACHINE LEARNING APPROACHES FOR EVALUATING STAT...

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. The book 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  the book 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
the book considers the IBM SPSS Modeler procedures as well as the respective models suggested
by this software. The book is read by students in production engineering  economics and
agricultural studies  public bodies and managers in the farming sector.

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