Semantic Scholar Open Access 2020 132 sitasi

Data science in economics: comprehensive review of advanced machine learning and deep learning methods

Saeed Nosratabadi A. Mosavi Puhong Duan Pedram Ghamisi Ferdinánd Filip +4 lainnya

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Abstrak

This paper provides a state-of-the-art investigation of advances in data science in emerging economic applications. The analysis was performed on novel data science methods in four individual classes of deep learning models, hybrid deep learning models, hybrid machine learning, and ensemble models. Application domains include a wide and diverse range of economics research from the stock market, marketing, and e-commerce to corporate banking and cryptocurrency. Prisma method, a systematic literature review methodology, was used to ensure the quality of the survey. The findings reveal that the trends follow the advancement of hybrid models, which, based on the accuracy metric, outperform other learning algorithms. It is further expected that the trends will converge toward the advancements of sophisticated hybrid deep learning models.

Topik & Kata Kunci

Computer Science

Penulis (9)

Saeed Nosratabadi

A. Mosavi

Puhong Duan

Pedram Ghamisi

Ferdinánd Filip

Shahab S. Band

U. Reuter

João Gama

Amir H. Gandomi

Format Sitasi

APA MLA BibTeX

Nosratabadi, S., Mosavi, A., Duan, P., Ghamisi, P., Filip, F., Band, S.S. et al. (2020). Data science in economics: comprehensive review of advanced machine learning and deep learning methods. https://doi.org/10.21203/rs.3.rs-91905/v1

Akses Cepat

Lihat di Sumber doi.org/10.21203/rs.3.rs-91905/v1

Informasi Jurnal

Tahun Terbit: 2020
Bahasa: en
Total Sitasi: 132×
Sumber Database: Semantic Scholar
DOI: 10.21203/rs.3.rs-91905/v1
Akses: Open Access ✓