| Autor: |
Ramdhani, Yudi, Prasetio, Rizki Tri, Hidayat, Ryan, Alamsyah, Doni Purnama |
| Předmět: |
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| Zdroj: |
Proceedings of the International Conference on Industrial Engineering & Operations Management; 11/3/2021, p3142-3149, 8p |
| Abstrakt: |
Cancer patients are usually advised to follow a number of treatments. Such as chemotherapy, radiotherapy, and surgery. Now increasingly popular is therapy with the method of immunotherapy. Immunotherapy is the latest breakthrough in cancer treatment. This therapy uses the body's own immune system to fight cancer cells. In this study, a comparison was made between the Support Vector Machine (SVM) algorithm and the Neural Network by using the Rapid Minner application and the Immunotherapy dataset, showing the results that the Neural Network has a higher accuracy value with an average accuracy value of 79.08%, 95.52%, 95.63% in three stages while for Support Vector Machine the average accuracy value is 78.22%, 83.82%, 86.48% in three successive stages from the results which concluded that the Neural Network has a higher level of accuracy than Support Vector Machine for Immunotherapy dataset classification, using the Genetic Algorithm Optimization Feature Proven effective in increasing the accuracy of both classification algorithms. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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