Entropy in Real-World Datasets and Its Impact on Machine Learning II
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Multidisciplinary Applications".
Deadline for manuscript submissions: 15 October 2024 | Viewed by 250
Special Issue Editors
2. Łukasiewicz Research Network - Institute of Innovative Technologies EMAG, 40-189 Katowice, Poland
Interests: machine learning; ensemble methods; decision trees; ant colony optimization; computational intelligence; data analysis; optimization
Special Issues, Collections and Topics in MDPI journals
Interests: cyber security; artificial intelligence; data security; automation; electric power engineering
Special Issue Information
Dear Colleagues,
Today, data science and machine learning remain pivotal pillars for solving the most intricate real-world challenges. Their versatility and utility span across various domains, including medicine, finance, text mining, image analysis, and more. Simultaneously, the abundance of user-accessible data continues to escalate, with concepts like big data and data streams garnering ever-increasing recognition. However, traditional classification methods may exhibit questionable efficacy in handling such data complexities, thereby necessitating continuous advancements in machine learning methodologies.
The second edition of this special session centers on the intricacies of real-world data and the impact of entropy on machine learning algorithms. Our particular focus lies on novel classification algorithms that harness the power of data science to model and process diverse real-world datasets effectively.
We welcome researchers to submit their original work, showcasing innovative approaches to data classification and analysis of real-world datasets, with a keen emphasis on entropy and its influence on machine learning effectiveness. We aim to foster a collaborative platform for exchanging knowledge and experiences related to cutting-edge developments in data science and data classification.
Prof. Dr. Jan Kozak
Dr. Artur Kozłowski
Dr. Barbara Probierz
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. Entropy 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 2600 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
- real-world datasets
- data science
- machine learning algorithms
- optimization
- classification
- prediction methods
- entropy in big data
Related Special Issue
- Entropy in Real-World Datasets and Its Impact on Machine Learning in Entropy (13 articles)
