| Model,Accuracy,Precision,Recall,F1,Type |
| SVM,0.6647043767596621,0.6793157076205287,0.8867235079171741,0.7692849594927792,Baseline |
| Logistic Regression,0.6606091630406962,0.6799620132953467,0.8721071863580999,0.7641408751334045,Baseline |
| Gradient Boosting,0.6644484259022267,0.6938088829071333,0.8371904181892001,0.7587856485740571,Baseline |
| AdaBoost,0.6570258510366009,0.6932874354561102,0.8177019894437678,0.7503725782414307,Baseline |
| Random Forest,0.6480675710263629,0.6903428971308607,0.8010556232237109,0.7415899267055065,Baseline |
| XGBoost,0.6501151778858459,0.6941885187810064,0.7953714981729598,0.7413434247871334,Baseline |
| Decision Tree,0.5963654978244177,0.677626303127506,0.6861550954120991,0.6818640306637079,Baseline |
| Random Forest,0.661121064755567,0.6724190130184681,0.901745838408445,0.7703780783905654,Tuned |
| Gradient Boosting,0.665984131046839,0.6905859117840685,0.8518067397482745,0.7627704053808398,Tuned |
| XGBoost,0.6667519836191451,0.6916474083856058,0.8505887129516849,0.7629278951201748,Tuned |
| SVM,0.6621448681853084,0.671673175127666,0.9078359723913926,0.7720994475138122,Tuned |
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