model | Accuracy | AUC | Recall | Precision | F1-score | Kappa | MCC |
---|---|---|---|---|---|---|---|
Ada Boost Classifier | 0.7894 | 0.7767 | 0.5484 | 0.7056 | 0.6049 | 0.4656 | 0.4799 |
Ridge Classifier | 0.7895 | 0.0000 | 0.5110 | 0.7214 | 0.5891 | 0.4536 | 0.4712 |
CatBoost Classifier | 0.7784 | 0.7672 | 0.4374 | 0.7160 | 0.5345 | 0.4023 | 0.4274 |
Light Gradient Boosting Machine | 0.7764 | 0.7498 | 0.5352 | 0.6486 | 0.5852 | 0.4347 | 0.4390 |
Linear Discriminant Analysis | 0.7813 | 0.5407 | 0.6580 | 0.6580 | 0.5878 | 0.4369 | 0.4445 |
Gradient Boosting Classifier | 0.7716 | 0.7437 | 0.4956 | 0.6523 | 0.5618 | 0.4118 | 0.4196 |
Extra Trees Classifier | 0.7627 | 0.7613 | 0.4143 | 0.6585 | 0.5048 | 0.3619 | 0.3797 |
Random Forest Classifier | 0.7626 | 0.7652 | 0.3978 | 0.6753 | 0.4952 | 0.3554 | 0.3788 |
K Neighbors Classifier | 0.7512 | 0.6783 | 0.3533 | 0.6517 | 0.4561 | 0.3138 | 0.3391 |
Extreme Gradient Boosting | 0.7403 | 0.7378 | 0.4511 | 0.5901 | 0.5054 | 0.3350 | 0.3436 |
Naive Bayes | 0.7266 | 0.7537 | 0.6297 | 0.5393 | 0.5785 | 0.3796 | 0.3833 |
Dummy Classifier | 0.7018 | 0.5000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 |
SVM - Linear Kermel | 0.6886 | 0.0000 | 0.5066 | 0.5422 | 0.4605 | 0.2624 | 0.2920 |
Decision Tree Classifier | 0.6371 | 0.5849 | 0.4445 | 0.4032 | 0.4181 | 0.1582 | 0.1603 |
Quadratic Discriminant Analysis | 0.5670 | 0.5271 | 0.4154 | 0.3138 | 0.3382 | 0.0406 | 0.0426 |