Supervised and Unsupervised Classification Algorithms

Dear Colleagues,

Supervised and unsupervised classification algorithms are the two main branches of machine learning methods. Supervised classification refers to the task of training a system using labeled data divided into classes, and assigning data to these existing classes. The process consists in computing a model from a set of labeled training data, and then applying the model to predict the class label for incoming unlabeled data. It is called supervised learning because the training data set supervises the learning process. Supervised classification algorithms are divided into two categories: classification and regression.

In unsupervised classification, the data being processed are unlabeled, so in the lack of prior knowledge, the algorithm tries to search for a similarity to generate clusters and assign classes. Unsupervised classification algorithms are divided into three categories: clustering, data estimation, and dimensionality reduction.

Applications range from object detection from biomedical images and disease prediction to natural language understanding and generation.

Submissions are welcome both for traditional classification problems as well as new applications. Potential topics include but are not limited to image classification, data integration, clustering approaches, feature extraction, etc.

Dr. Mario Rosario Guarracino
Dr. Laura Antonelli
Dr. Pietro Hiram Guzzi
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 250 words) can be sent to the Editorial Office for assessment.

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. Algorithms 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 1800 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.