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Table 1.

Failure dataset description.

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Table 1 Expand

Table 2.

Key performance metrics comparison.

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Table 2 Expand

Fig 1.

Curve ROC of the base logistic regression model.

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Fig 1 Expand

Table 3.

Confusion matrix for training and test data set.

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Table 3 Expand

Fig 2.

Curve ROC of the training and test dataset without SMOTE.

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Fig 2 Expand

Table 4.

Comparison of the base model versus smote-enhanced.

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Table 4 Expand

Fig 3.

Curve ROC of training and test dataset with SMOTE.

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Fig 3 Expand

Table 5.

Train and test classification evaluation metrics.

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Table 6.

Confusion matrix training and test data set.

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Table 7.

Training and test classification evaluation metrics with SMOTE.

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Fig 4.

Random Forest and Gradient Boosting algorithms.

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Fig 5.

Random forest search and optimization technique.

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Fig 6.

Gradient boosting search and optimization technique.

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Table 8.

Predict Class SMOTE vs ARGM.

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Table 9.

SMOTE vs ARGM ranking evaluation metrics.

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Fig 7.

ROC curve, SMOTE versus ARGM.

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Table 10.

Micro financial institutions assessed with RGCM.

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