Model Accuracy Balanced Accuracy Log Loss AUC XG Boost 83% 76% 0.41 0.87 Random Forest 77% 63% 0.47 0.81 Logistic Regres

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answerhappygod
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Model Accuracy Balanced Accuracy Log Loss AUC XG Boost 83% 76% 0.41 0.87 Random Forest 77% 63% 0.47 0.81 Logistic Regres

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Model Accuracy Balanced Accuracy Log Loss Auc Xg Boost 83 76 0 41 0 87 Random Forest 77 63 0 47 0 81 Logistic Regres 1
Model Accuracy Balanced Accuracy Log Loss Auc Xg Boost 83 76 0 41 0 87 Random Forest 77 63 0 47 0 81 Logistic Regres 1 (359.38 KiB) Viewed 120 times
Model Accuracy Balanced Accuracy Log Loss AUC XG Boost 83% 76% 0.41 0.87 Random Forest 77% 63% 0.47 0.81 Logistic Regression 74% 64% 0.65 0.65 Decision Tree 72% 66% 1.63 0.6 Based on Log Loss only, which model will you chose for classification XG Boost Random Forest Logistic Regression Decision Tree
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