Machine-Learning Techniques in Economics: New Tools for Predicting Economic Growth

By Atin Basuchoudhary, Tinni Sen, James T. Bang

Offers a guide to how machine learning techniques can improve predictive power in answering economic questions
Provides R codes to help guide the researcher in applying machine learning techniques using the R package

Uses partial dependence plots to tease out non-linear effects of explanatory variables on the dependent variables

• Format: Paperback
• Language: English
• ISBN: 3319690132
• ISBN13: 9783319690131
• Release Date: January 2018
• Publisher: Springer
• Length: 94 Pages
• Weight: 0.33 lbs.
• Dimensions: 0.2" x 6.1" x 9.2"