add cutomized training

python/xgboost_python.h

@@ -127,6 +127,19 @@ extern "C"{
      * \param dtrain training data
      */        
     void XGBoosterUpdateOneIter( void *handle, void *dtrain );   
+    
+    /*!
+     * \brief update the model, by directly specify gradient and second order gradient, 
+     *        this can be used to replace UpdateOneIter, to support customized loss function
+     * \param handle handle
+     * \param dtrain training data
+     * \param grad gradient statistics
+     * \param hess second order gradient statistics
+     * \param len length of grad/hess array
+     * \param bst_group boost group we are working at, default = -1
+     */
+    void XGBoosterBoostOneIter( void *handle, void *dtrain, 
+                                float *grad, float *hess, size_t len, int bst_group );   
     /*! 
      * \brief print evaluation statistics to stdout for xgboost
      * \param handle handle
@@ -141,8 +154,9 @@ extern "C"{
      * \param handle handle
      * \param dmat data matrix
      * \param len used to store length of returning result
+     * \param bst_group booster group, if model contains multiple booster group, default = -1 means predict for all groups 
      */    
-    const float *XGBoosterPredict( void *handle, void *dmat, size_t *len );
+    const float *XGBoosterPredict( void *handle, void *dmat, size_t *len, int bst_group );
     /*! 
      * \brief load model from existing file
      * \param handle handle