model_history, ITER_HP, settings in AutoML(), checkpoint bug fix (#283)

if save_best_model_per_estimator is False and retrain_final is True, unfit the model after evaluation in HPO.
retrain if using ray.
update ITER_HP in config after a trial is finished.
change prophet logging level.
example and notebook update.
allow settings to be passed to AutoML constructor. Are you planning to add multi-output-regression capability to FLAML #192 Is multi-tasking allowed? #277 can pass the auotml setting to the constructor instead of requiring a derived class.
remove model_history.
checkpoint bug fix.

* model_history meaning save_best_model_per_estimator

* ITER_HP

* example update

* prophet logging level

* comment update in forecast notebook

* print format improvement

* allow settings to be passed to AutoML constructor

* checkpoint bug fix

* time limit for autohf regression test

* skip slow test on macos

* cleanup before del

notebook/flaml_forecast.ipynb

@@ -119,9 +119,9 @@
    "source": [
     "'''The main flaml automl API'''\n",
     "automl.fit(dataframe=train_df,  # training data\n",
-    "           label='co2',  # For 'forecast' task, label should be a tuple of strings for timestamp and value columns\n",
-    "           **settings, \n",
-    "           period=time_horizon)  # key word argument 'period' must be included for forecast task)"
+    "           label='co2',  # label column\n",
+    "           period=time_horizon,  # key word argument 'period' must be included for forecast task)\n",
+    "           **settings)"
    ]
   },
   {
@@ -173,8 +173,8 @@
    "source": [
     "''' compute predictions of testing dataset '''\n",
     "flaml_y_pred = automl.predict(X_test)\n",
-    "print('Predicted labels', flaml_y_pred)\n",
-    "print('True labels', y_test)"
+    "print(f\"Predicted labels\\n{flaml_y_pred}\")\n",
+    "print(f\"True labels\\n{y_test}\")"
    ]
   },
   {