Machine Learning Evaluation Metrics

Accuracy | Accuracy |

Area_Under_Curve | Calculate the Area Under the Curve |

AUC | Area Under the Receiver Operating Characteristic Curve (ROC... |

ConfusionDF | Confusion Matrix (Data Frame Format) |

ConfusionMatrix | Confusion Matrix |

F1_Score | F1 Score |

FBeta_Score | F-Beta Score |

GainAUC | Area Under the Gain Chart |

Gini | Gini Coefficient |

KS_Stat | Kolmogorov-Smirnov Statistic |

LiftAUC | Area Under the Lift Chart |

LogLoss | Log loss / Cross-Entropy Loss |

MAE | Mean Absolute Error Loss |

MAPE | Mean Absolute Percentage Error Loss |

MedianAE | Median Absolute Error Loss |

MedianAPE | Median Absolute Percentage Error Loss |

MLmetrics | MLmetrics: Machine Learning Evaluation Metrics |

MSE | Mean Square Error Loss |

MultiLogLoss | Multi Class Log Loss |

NormalizedGini | Normalized Gini Coefficient |

Poisson_LogLoss | Poisson Log loss |

PRAUC | Area Under the Precision-Recall Curve (PR AUC) |

Precision | Precision |

R2_score | R-Squared (Coefficient of Determination) Regression Score |

RAE | Relative Absolute Error Loss |

Recall | Recall |

RMSE | Root Mean Square Error Loss |

RMSLE | Root Mean Squared Logarithmic Error Loss |

RMSPE | Root Mean Square Percentage Error Loss |

RRSE | Root Relative Squared Error Loss |

Sensitivity | Sensitivity |

Specificity | Specificity |

ZeroOneLoss | Normalized Zero-One Loss (Classification Error Loss) |

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