More formally, every machine learning algorithm depends on 3 things which need to be able to be programmed. First … general, a machine learning algorithm attempts to find it's own rules and methods in order to optimize its performance measure …

), machine learning (ML) and deep learning (DL) use: by businesses for predictive analytics, process optimisation and market … summarises theoretical and empirical evidence, considers how specific business machine learning methods may affect AC and whether … and competition/consumer protection policy.Much early ML literature concentrated programmes ‘learning’ about their …

Predictive power has always been the main research focus of learning algorithms with the goal of minimizing the test … on sparse learning in order to avoid overfitting which can greatly affect the accuracy of out-of-sample prediction … response whereas even sparse-learning methods can still preserve a high number of attributes in high-dimensional settings and …

This paper consolidates recent methodological developments based on Double Machine Learning (DML) with a focus on …