Prognosis of Thoracic Cancer Using the Bierman Random Committee Machine Learning
DOI:
https://doi.org/10.3991/ijoe.v17i12.27573Keywords:
Thoracic Cancer, Random Committee forest, Machine learning algorithm.Abstract
Thoracic most cancers are a prime problem in the clinical field. Unexpected occur-ring cannot be predicted earlier but if the strategy is fine-tuned properly then the prognosis of cancer is not a major issue. But the problem is how to find out the proper layout with all possible features. The sector of Thoracic Surgery is offering a source of the dataset with all feasible attributes of thoracic cancer. All the features suggested by this medical sector were approved by the Consortium of Tuberculosis and Pulmonary Diseases. The random committee is a novel hybrid algorithm that utilizes the benefit of both random forests with committee concepts. Many random forests are created as the result of the iteration. But anyone can be created and the committee analyses and retains any one optimal solution. Brei man, the first researcher to propose the general concept of Radio Frequency following the same he proposed the famous and most popular forest RF algorithm.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2021 Ezzat A. Mansour
This work is licensed under a Creative Commons Attribution 4.0 International License.
The submitting author warrants that the submission is original and that she/he is the author of the submission together with the named co-authors; to the extend the submission incorporates text passages, figures, data or other material from the work of others, the submitting author has obtained any necessary permission.
Articles in this journal are published under the Creative Commons Attribution Licence (CC-BY What does this mean?). This is to get more legal certainty about what readers can do with published articles, and thus a wider dissemination and archiving, which in turn makes publishing with this journal more valuable for you, the authors.
By submitting an article the author grants to this journal the non-exclusive right to publish it. The author retains the copyright and the publishing rights for his article without any restrictions.