Configuration for init estimation. (#8343)

* Configuration for init estimation.

* Check whether the model needs configuration based on const attribute `ModelFitted`
instead of a mutable state.
* Add parameter `boost_from_average` to tell whether the user has specified base score.
* Add tests.

include/xgboost/gbm.h

@@ -75,6 +75,11 @@ class GradientBooster : public Model, public Configurable {
   /*! \brief Return number of boosted rounds.
    */
   virtual int32_t BoostedRounds() const = 0;
+  /**
+   * \brief Whether the model has already been trained. When tree booster is chosen, then
+   *        returns true when there are existing trees.
+   */
+  virtual bool ModelFitted() const = 0;
   /*!
    * \brief perform update to the model(boosting)
    * \param p_fmat feature matrix that provide access to features

include/xgboost/learner.h

@@ -328,7 +328,7 @@ struct LearnerModelParam {
   void Copy(LearnerModelParam const& that);
 
   /* \brief Whether this parameter is initialized with LearnerModelParamLegacy. */
-  bool Initialized() const { return num_feature != 0; }
+  bool Initialized() const { return num_feature != 0 && num_output_group != 0; }
 };
 
 }  // namespace xgboost