Research Article
Identification of Dry Bean Varieties Based on Multiple Attributes Using CatBoost Machine Learning Algorithm
Table 6
Performance comparison with the existing method with 80 : 20 split.
| Models | ML algorithms | Precision | Recall | f1-score | Accuracy in percentage |
| Koklu and Ozkan [11] | MLP | 0.93 | 0.93 | 0.93 | 91.73 | SVM | 0.94 | 0.94 | 0.94 | 93.13 | DT | 0.89 | 0.88 | 0.88 | 87.92 | kNN | 0.93 | 0.93 | 0.93 | 92.52 |
| Proposed method | Random forest | 0.93 | 0.93 | 0.93 | 93.29 | XGBoost | 0.93 | 0.93 | 0.93 | 93.57 | CatBoost | 0.94 | 0.94 | 0.94 | 94.25 |
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