Predictive Analytics and Data Science
A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Processes".
Deadline for manuscript submissions: closed (20 April 2023) | Viewed by 68650
Special Issue Editors
Interests: machine learning; data mining; predictive analytics; artificial intelligence; neural networks; network analysis; data science; healthcare data mining
Special Issues, Collections and Topics in MDPI journals
Interests: chemical engineering; complex systems; computational intelligence; network science; process engineering
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The development and maintenance of predictive data-driven models poses several challenges, such as feature selection, model structure optimization, sensitivity analysis, model validation, model maintenance, transfer learning and adaptation, model deployment, and evaluation of the benefit of the application of the models.
This Special Issue solicits papers covering the development, validation, application, and maintenance of predictive analytics models and presenting real-life applications. The potential topics include but are not limited to:
- Classification-based prediction models;
- Regression-based prediction models;
- Forecast using deep learning methods and algorithms;
- Managing the uncertainty and missing data in forecast;
- The life cycle of predictive models, and maintaining predictive models;
- Development and validation of online predictive models;
- Self-learning predictive models;
- Predictive analytics in Industry 4.0 (application of sensors, historical experience);
- Predictive analysis in healthcare and economy (e.g. patient pathway prediction, predicting complications, customer relationship management, risk reduction, churn prevention, market trend and analysis, credit scoring);
- Social media and text analysis-based predictive models and systems.
Dr. Agnes Vathy-Fogarassy
Prof. Dr. Janos Abonyi
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- classification
- regression
- deep learning
- uncertainty
- validation and maintenance
- self-learning
- real-life applications
Related Special Issue
- Second Edition of Predictive Analytics and Data Science in Information (5 articles)