PUBDEV-8547 - eif scoring history - add score_each_iteration and scor…

…e_tree_interval to the documentation
h2oai · Nov 9, 2023 · 91868be · 91868be
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diff --git a/h2o-docs/src/product/data-science/algo-params/score_each_iteration.rst b/h2o-docs/src/product/data-science/algo-params/score_each_iteration.rst
@@ -3,7 +3,7 @@
 ``score_each_iteration``
 ------------------------
 
-- Available in: GBM, DRF, Deep Learning, GLM, GAM, PCA, GLRM, Naïve-Bayes, K-Means, XGBoost, Isolation Forest, Uplift DRF
+- Available in: GBM, DRF, Deep Learning, GLM, GAM, PCA, GLRM, Naïve-Bayes, K-Means, XGBoost, Isolation Forest, Extended Isolation Forest, Uplift DRF
 - Hyperparameter: no
 
 

diff --git a/h2o-docs/src/product/data-science/algo-params/score_tree_interval.rst b/h2o-docs/src/product/data-science/algo-params/score_tree_interval.rst
@@ -3,7 +3,7 @@
 ``score_tree_interval``
 ------------------------
 
-- Available in: GBM, DRF, XGBoost, Isolation Forest, Uplift DRF
+- Available in: GBM, DRF, XGBoost, Isolation Forest, Extended Isolation Forest, Uplift DRF
 - Hyperparameter: no
 
 Description
@@ -84,4 +84,4 @@ Example
 		cars_gbm.train(x = predictors, y = response, training_frame = train, validation_frame = valid)
 
 		# print the model score every 5 trees
-		cars_gbm.scoring_history()
+		cars_gbm.scoring_history()
diff --git a/h2o-docs/src/product/data-science/eif.rst b/h2o-docs/src/product/data-science/eif.rst
@@ -58,6 +58,8 @@ Shared tree-algorithm parameters
 
 -  `ntrees <algo-params/ntrees.html>`__: Specify the number of trees. This option defaults to ``100``.
 
+-  `score_tree_interval <algo-params/score_tree_interval.html>`__: Score the model after every so many trees. This value is set to 0 (disabled) by default.
+
 Common parameters
 '''''''''''''''''
 
@@ -77,6 +79,8 @@ Common parameters
 
 -  `model_id <algo-params/model_id.html>`__: Specify a custom name for the model to use as a reference. By default, H2O automatically generates a destination key.
 
+-  `score_each_iteration <algo-params/score_each_iteration.html>`__: (Optional) Enable this option to score during each iteration of the model training (disabled by default).
+
 -  `seed <algo-params/seed.html>`__: Specify the random number generator (RNG) seed for algorithm components dependent on randomization. The seed is consistent for each H2O instance so that you can create models with the same starting conditions in alternative configurations. This option defaults to ``-1`` (time-based random number).
 
 -  `training_frame <algo-params/training_frame.html>`__: *Required* Specify the dataset used to build the model.