Hi everyone,

I’ve been trying to run this tutorial for Accelerated Failure Time in survival analysis.

When I run the following example:

```
import numpy as np
import xgboost as xgb
# 4-by-2 Data matrix
X = np.array([[1, -1], [-1, 1], [0, 1], [1, 0]])
dtrain = xgb.DMatrix(X)
# Associate ranged labels with the data matrix.
# This example shows each kind of censored labels.
# uncensored right left interval
y_lower_bound = np.array([ 2.0, 3.0, -np.inf, 4.0])
y_upper_bound = np.array([ 2.0, +np.inf, 4.0, 5.0])
dtrain.set_float_info('label_lower_bound', y_lower_bound)
dtrain.set_float_info('label_upper_bound', y_upper_bound)
```

I get the error “Unknown metainfo: label_lower_bound”. I’m aware that the AFL model is a new addition to XGBoost, I just want to know if the current version supports upper and lower labels in a DMatrix yet (since it’s used in the tutorial provided by XGBoost).

Any clarity will be much appreciated.

Carl