fix convert signature (#80)

* fix convert signature

* bump version

README.md

@@ -409,7 +409,7 @@ To cite this repository:
   author = {Davi Vieira and Gabriel Gimenez and Guilherme Marmerola and Vitor Estima},
   title = {XGBoost Survival Embeddings: improving statistical properties of XGBoost survival analysis implementation},
   url = {http://github.com/loft-br/xgboost-survival-embeddings},
-  version = {0.3.2},
+  version = {0.3.3},
   year = {2021},
 }
 ```

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "xgbse"
-version = "0.3.2"
+version = "0.3.3"
 description = "Improving XGBoost survival analysis with embeddings and debiased estimators"
 authors = ["Loft Data Science Team <bandits@loft.com.br>"]
 readme = "README.md"

xgbse/__init__.py

@@ -5,7 +5,7 @@
 from ._meta import XGBSEBootstrapEstimator
 from ._stacked_weibull import XGBSEStackedWeibull
 
-__version__ = "0.3.2"
+__version__ = "0.3.3"
 
 __all__ = [
     "XGBSEDebiasedBCE",

xgbse/converters.py

@@ -42,7 +42,7 @@ def convert_y(y):
     return y[event_field], y[time_field]
 
 
-def convert_data_to_xgb_format(X, y, objective, enable_categorical: bool):
+def convert_data_to_xgb_format(X, y, objective, enable_categorical: bool = False):
     """Convert (X, y) data format to xgb.DMatrix format, either using cox or aft models.
 
     Args:
@@ -51,6 +51,7 @@ def convert_data_to_xgb_format(X, y, objective, enable_categorical: bool):
         y (structured array(numpy.bool_, numpy.number)): binary event indicator as first field,
             and time of event or time of censoring as second field.
         objective (string): one of 'survival:aft' or 'survival:cox'
+        enable_categorical (bool): whether to enable categorical features - default is False
 
     Returns:
         xgb.DMatrix: data to train xgb