Search Results - subject:"Learning Process"

Counterfactual synthetic minority oversampling technique : solving healthcare's imbalanced learning challenge

Almeida, Goncalo; Bacao, Fernando - In: Data science and management : DSM 8 (2025) 4, pp. 436-446

The application of machine learning in the healthcare domain has groundbreaking potential across a wide range of scenarios. However, this potential is often stalled by data-related challenges, such as the imbalanced nature of the domain's data, where critical outcomes tend to be inherently rare....

Persistent link: https://www.econbiz.de/10015638964

Personality traits, remote work and productivity

Gavoille, Nicolas; Hazans, Mihails - In: International labour review 164 (2025) 3, pp. 1-19

This article investigates the link between personality traits and workers' productivity when working from home (WFH). We exploit a survey conducted in Latvia in 2021, providing measures of the "Big Five" personality traits for more than 1,700 recent teleworkers. Other things being equal,...

Persistent link: https://www.econbiz.de/10015553683

Learning to be rational in the presence of news : a lab investigation

Lustenhouwer, Joep; Salle, Isabelle - In: European economic review : EER 172 (2025), pp. 1-20

We conduct a laboratory experiment in a micro-founded macroeconomic model where participants receive public announcements about future government spending shocks, and are tasked with repeatedly forecasting output over a given horizon. By eliciting several-period-ahead predictions, we can...

Persistent link: https://www.econbiz.de/10015580501

Who's on FIRE? : household characteristics and the formation of inflation expectations

Reiche, Lovisa; Galati, Gabriele; Moessner, Richhild; … - 2025

Persistent link: https://www.econbiz.de/10015556787

Unlocking the power of machine learning in big data : a scoping survey

Surur, Fadil Mohammed; Mamo, Abiy Abinet; … - In: Data science and management : DSM 8 (2025) 4, pp. 519-535

Machine learning (ML) plays a crucial role in big data (BD) by serving as the cornerstone of efficient data processing and analysis. In particular, ML provides BD with the ability to extract valuable insights from the large data sets. Therefore, this study conducted a scoping survey to define...

Persistent link: https://www.econbiz.de/10015639119

Dynamic complementarity

Heckman, James J.; Tian, Haihan; Zhang, Zijian; Zhou, Jin - 2025

Dynamic complementarity is the concept that past investments that lead to higher stocks of skill at an age, promote the growth of skills from investment at that age. We define and produce evidence on dynamic complementarity and its three components using unique Chinese data from a home visiting...

Persistent link: https://www.econbiz.de/10015650913

You learn when it hurts : evidence in the mutual fund industry

Gimeno, Ruth; Sarto, José Luis; Vicente, Luis - In: Journal of risk and financial management : JRFM 15 (2022) 1, pp. 1-29

This paper aims to contribute to the lack of research on the learning process of mutual fund markets. The empirical …, such as the concentration and the banking control of the industry, which may affect the learning process. Our main … in the percentage of important trading errors over time, thereby providing evidence of the global learning process of the …

Persistent link: https://www.econbiz.de/10012814154

Entrepreneurship competence model for supporting learners development at all educational levels

Venesaar, Urve; Malleus, Elina; Arro, Grete; Toding, Martin - In: Administrative Sciences : open access journal 12 (2022) 1, pp. 1-29

The development of entrepreneurship competence considering a broad view of entrepreneurship requires a systematic approach to determine the validated content of learning and methodological basis for supporting learners' entrepreneurial attitudes and behaviour. There is still relatively little...

Persistent link: https://www.econbiz.de/10012816276

Lumpy forecasts

Baley, Isaac; Turen, Javier - 2024

Persistent link: https://www.econbiz.de/10015375202

A review of unsupervised k-value selection techniques in clustering algorithms

Pegado-Bardayo, Ana; Lorenzo-Espejo, Antonio; … - In: Journal of industrial engineering and management : JIEM 17 (2024) 3, pp. 641-649

Purpose: Automatic grouping of data according to certain characteristics is made possible by clustering algorithms, which makes them an essential tool when working with large datasets. However, although they are unsupervised tools, they generally require the specification of the number of...

Persistent link: https://www.econbiz.de/10015376973