Analysis of Tumor Classification Algorithms for Breast Cancer Prediction by Machine Learning Methods

Authors

  • Nataliya Boyko Lviv Polytechnic National University
  • Olena Kulchytska Lviv Polytechnic National University

DOI:

https://doi.org/10.31713/MCIT.2021.07

Keywords:

big data, data mining, machine learning

Abstract

The paper presents machine learning methods for classification and forecasting problems. Tumor classification algorithms based on the Random Forest method are considered. To understand the distribution of classified data, a 3D graph of the three attributes of the date set was implemented. For a better understanding, graphs were constructed, namely the ROC curve and the RP curve. The AUC value for the model was also determined. The results of the graphs and AUC values ​​were compared with the NoSkill model, ie the model without skills. High quality of the received models is offered.

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Published

2021-11-21

How to Cite

Boyko, N., & Kulchytska, O. (2021). Analysis of Tumor Classification Algorithms for Breast Cancer Prediction by Machine Learning Methods. Modeling, Control and Information Technologies, (5), 29–32. https://doi.org/10.31713/MCIT.2021.07

Issue

No. 5 (2021): Modeling, control and information technologies

Section

index

License

Copyright (c) 2021 Modeling, Control and Information Technologies: Proceedings of International scientific and practical conference

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

All materials are distributed under the terms of the Creative Commons Attribution 4.0 International License, which allows others to distribute the work with attribution to the authorship of this work and the first publication in this journal.