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Evaluating Performance of Regression Machine Learning Models Using Multiple Error Metrics in Azure Machine Learning Studio
Botchkarev, Alexei - 2018
Data driven companies effectively use regression machine learning methods for making predictions in many sectors. Cloud-based Azure Machine Learning Studio (MLS) has a potential of expediting machine learning experiments by offering a convenient and powerful integrated development environment....
Persistent link: https://www.econbiz.de/10012919484
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Reinforcement Learning : An Artificial Intelligence Approach to Forecasting when There Are Structural Breaks
Marcondes, Jeronymo; Marçal, Emerson Fernandes - 2023
Economic forecasting during structural breaks is challenging due to the possible systematic failure of existent models. Robust forecast devices are able to provide unbiased forecasts just after structural change but at the cost of higher variance in normal times. Reinforcement learning (RL)...
Persistent link: https://www.econbiz.de/10014261004
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What does economics assume about people's knowledge? : who knows?
Caleiro, António - 2007 - 1st version: April 15, 2007, this version: October 16, 2007
rationality behaviour by people. Quite recent developments in the Economics of Knowledge, i.e. the so-called learning models, have …
Persistent link: https://www.econbiz.de/10011502970
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Is bounded rationality a capacity, enabling learning?
Novarese, Marco - 2009
This papers contributes to the stream of research on rule based behavior, and rationality. A bounded rational agent can … Ecological rationality, yet, evidences the possible advantage of using a limited amount of information. The present paper takes a … hypothesis to be continuously tested. This vision of bounds and learning has many implications for the debate on rationality and …
Persistent link: https://www.econbiz.de/10011523697
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Deeply Learning Derivatives
Ferguson, Ryan - 2018
This paper uses deep learning to value derivatives. The approach is broadly applicable, and we use a call option on a basket of stocks as an example. We show that the deep learning model is accurate and very fast, capable of producing valuations a million times faster than traditional models. We...
Persistent link: https://www.econbiz.de/10012911647
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Agent-based model calibration using machine learning surrogates
Lamperti, Francesco; Roventini, Andrea; Sani, Amir - 2017
Taking agent-based models (ABM) closer to the data is an open challenge. This paper explicitly tackles parameter space exploration and calibration of ABMs combining supervised machine-learning and intelligent sampling to build a surrogate meta-model. The proposed approach provides a fast and...
Persistent link: https://www.econbiz.de/10011630888
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Swag: a wrapper method for sparse learning
Molinari, Roberto; Bakalli, Gaetan; Guerrier, Stéphane; … - 2020
Predictive power has always been the main research focus of learning algorithms with the goal of minimizing the test error for supervised classification and regression problems. While the general approach for these algorithms is to consider all possible attributes in a dataset to best predict...
Persistent link: https://www.econbiz.de/10012270791
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Benchmarking Econometric and Machine Learning Methodologies in Nowcasting
Hopp, Daniel - 2022
Nowcasting can play a key role in giving policymakers timelier insight to data published with a significant time lag, such as final GDP figures. Currently, there are a plethora of methodologies and approaches for practitioners to choose from. However, there lacks a comprehensive comparison of...
Persistent link: https://www.econbiz.de/10014084603
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Cognitive Economics
Walliser, Bernard (contributor) - 2008
Written in an informal way, this book is addressed to philosophers or cognitive scientists curious of how economics deals with cognition and to graduate students in economics eager to discover how economics evolves. It aims at extending the framework of game theory in order to better fit with...
Persistent link: https://www.econbiz.de/10013520755
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Cognitive economics
Walliser, Bernard - 2008 - 1. ed.
Persistent link: https://www.econbiz.de/10003463313