ht/built gradle

h2oai · Aug 14, 2024 · 8cc37b2 · 8cc37b2
1 parent 8dd67d2
commit 8cc37b2
Showing 1 changed file with 5 additions and 4 deletions.
diff --git a/h2o-py/h2o/estimators/decision_tree.py b/h2o-py/h2o/estimators/decision_tree.py
@@ -116,6 +116,7 @@ def ignore_const_cols(self):
         >>> prostate = h2o.import_file("http://s3.amazonaws.com/h2o-public-test-data/smalldata/prostate/prostate.csv")
         >>> target_variable = 'CAPSULE'
         >>> prostate[target_variable] = prostate[target_variable].asfactor()
+        >>> prostate["const_1"] = 6
         >>> train, test = prostate.split_frame(ratios=[0.7])
         >>> sdt_h2o = H2ODecisionTreeEstimator(model_id="decision_tree.hex",
         ...                                    max_depth=5,
@@ -145,11 +146,12 @@ def categorical_encoding(self):
         >>> h2o.init()
         >>> prostate = h2o.import_file("http://s3.amazonaws.com/h2o-public-test-data/smalldata/prostate/prostate.csv")
         >>> target_variable = 'CAPSULE'
+        >>> prostate["RACE"] = prostate["RACE"].asfactor()
         >>> prostate[target_variable] = prostate[target_variable].asfactor()
         >>> train, test = prostate.split_frame(ratios=[0.7])
         >>> sdt_h2o = H2ODecisionTreeEstimator(model_id="decision_tree.hex",
         ...                                    max_depth=5,
-        ...                                    categorical_encoding="auto")
+        ...                                    categorical_encoding="binary")
         >>> sdt_h2o.train(y=target_variable, training_frame=train)
         >>> pred_test = sdt_h2o.predict(test)
         """
@@ -205,8 +207,7 @@ def max_depth(self):
         >>> prostate[target_variable] = prostate[target_variable].asfactor()
         >>> train, test = prostate.split_frame(ratios=[0.7])
         >>> sdt_h2o = H2ODecisionTreeEstimator(model_id="decision_tree.hex",
-        ...                                    max_depth=5,
-        ...                                    max_depth=20)
+        ...                                    max_depth=5)
         >>> sdt_h2o.train(y=target_variable, training_frame=train)
         >>> pred_test = sdt_h2o.predict(test)
         """
@@ -235,7 +236,7 @@ def min_rows(self):
         >>> train, test = prostate.split_frame(ratios=[0.7])
         >>> sdt_h2o = H2ODecisionTreeEstimator(model_id="decision_tree.hex",
         ...                                    max_depth=5,
-        ...                                    min_rows=10)
+        ...                                    min_rows=20)
         >>> sdt_h2o.train(y=target_variable, training_frame=train)
         >>> pred_test = sdt_h2o.predict(test)
         """