An investigation of ensemble learning methods in classification problems and an application on non-small-cell lung cancer data
This study aims to classify NSCLC death status and consists of patient records of 24 variables created by the open-source dataset of the cancer data site. Besides, basic classifiers such as SMO (Sequential Minimal Optimization), K-NN (K-Nearest Neighbor), random forest, and XGBoost (Extreme Gradient...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Society of Turaz Bilim
2022-06-01
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| Series: | Medicine Science |
| Subjects: | |
| Online Access: | http://www.ejmanager.com/fulltextpdf.php?mno=119680 |