eval_metric_sur {BioPred} | R Documentation |

## Evaluation Metrics for XGBoostSub_sur Model

### Description

Function for evaluating XGBoostSub_sur model performance.

### Usage

```
eval_metric_sur(
model,
X_feature,
y_label,
pi,
trt,
censor,
Loss_type = "A_learning"
)
```

### Arguments

`model` |
The trained XGBoostSub_sur model object. |

`X_feature` |
The input features matrix. |

`y_label` |
The input y matrix. |

`pi` |
The propensity scores vector, which should range from 0 to 1, representing the probability of assignment to treatment. |

`trt` |
The treatment indicator vector. Should take values of 1 or -1, where 1 represents the treatment group and -1 represents the control group. |

`censor` |
The censor status vector. Should take values of 1 or 0, where 1 represents censoring and 0 represents an observed event. |

`Loss_type` |
Type of loss function to use: "A_learning" or "Weight_learning". |

### Details

eval_metric: Function for Evaluating XGBoostSub_con Model Performance

This function evaluates the performance of an XGBoostSub_con model using a A-learning or weight-learning function.

### Value

Evaluation result of the XGBoostSub_sur model.

*BioPred*version 1.0.1 Index]