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This book helps and promotes the use of machine learning tools and
techniques in econometrics and explains how machine learning can
enhance and expand the econometrics toolbox in theory and in
practice. Throughout the volume, the authors raise and answer six
questions: 1) What are the similarities between existing
econometric and machine learning techniques? 2) To what extent can
machine learning techniques assist econometric investigation?
Specifically, how robust or stable is the prediction from machine
learning algorithms given the ever-changing nature of human
behavior? 3) Can machine learning techniques assist in testing
statistical hypotheses and identifying causal relationships in 'big
data? 4) How can existing econometric techniques be extended by
incorporating machine learning concepts? 5) How can new econometric
tools and approaches be elaborated on based on machine learning
techniques? 6) Is it possible to develop machine learning
techniques further and make them even more readily applicable in
econometrics? As the data structures in economic and financial data
become more complex and models become more sophisticated, the book
takes a multidisciplinary approach in developing both disciplines
of machine learning and econometrics in conjunction, rather than in
isolation. This volume is a must-read for scholars, researchers,
students, policy-makers, and practitioners, who are using
econometrics in theory or in practice.
The Business of Mining complete set of three Focus books will
provide readers with a holistic all-embracing appraisal of the
analytical tools available for assessing the economic viability of
prospective mines. Each volume has a discrete focus. This second
volume discusses, in some depth, alternative means of assessing the
economic viability of mining projects based on the best estimate of
the recoverable mineral and/or fossil fuel reserves. The books were
written primarily for undergraduate applied geologists, mining
engineers and extractive metallurgists and those pursuing
course-based postgraduate programs in mineral economics. However,
the complete series will also be an extremely useful reference text
for practicing mining professionals as well as for consultant
geologists, mining engineers or primary metallurgists.
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