use real tribuo RandomForest model

scicloj · Dec 27, 2024 · 5aa64ec · 5aa64ec
1 parent 24b42f8
commit 5aa64ec
Showing 1 changed file with 22 additions and 9 deletions.
diff --git a/notebooks/noj_book/automl.clj b/notebooks/noj_book/automl.clj
@@ -334,22 +334,34 @@ logistic-regression-specs
 ;; The list of the model types we want to try:
 (def models-specs 
   (concat logistic-regression-specs
-          [{:model-type :xgboost/classification :round 10}
+          [{:model-type :scicloj.ml.tribuo/classification
+            :tribuo-components [{:name "cart"
+                                 :type "org.tribuo.classification.dtree.CARTClassificationTrainer"
+                                 :properties {:maxDepth "8"
+                                              :useRandomSplitPoints "false"
+                                              :fractionFeaturesInSplit "0.5"}}
+                                {:name "combiner"
+                                 :type "org.tribuo.classification.ensemble.VotingCombiner"}
+
+                                {:name "random-forest"
+                                 :type "org.tribuo.common.tree.RandomForestTrainer"
+                                 :properties {:innerTrainer "cart"
+                                              :combiner "combiner"
+                                              :seed "1234"
+                                              :numMembers "500"}}]
+            :tribuo-trainer-name "random-forest"}
+
+           {:model-type :xgboost/classification :round 10}
            {:model-type :sklearn.classification/decision-tree-classifier}
            {:model-type :sklearn.classification/logistic-regression}
            {:model-type :sklearn.classification/random-forest-classifier}
            {:model-type :metamorph.ml/dummy-classifier}
            {:model-type :scicloj.ml.tribuo/classification
             :tribuo-components [{:name "logistic"
-                                 :type "org.tribuo.classification.sgd.linear.LinearSGDTrainer"}]
+                                 :type "org.tribuo.classification.sgd.linear.LogisticRegressionTrainer"}]
             :tribuo-trainer-name "logistic"}
-           {:model-type :scicloj.ml.tribuo/classification
-            :tribuo-components [{:name "random-forest"
-                                 :type "org.tribuo.classification.dtree.CARTClassificationTrainer"
-                                 :properties {:maxDepth "8"
-                                              :useRandomSplitPoints "false"
-                                              :fractionFeaturesInSplit "0.5"}}]
-            :tribuo-trainer-name "random-forest"}]))
+
+           ]))
 
 
 ;;  This uses models from Smile, Tribuo and sklearn but could be any
@@ -374,6 +386,7 @@ logistic-regression-specs
 ;; Execute all pipelines for all splits in the  cross-validations
 ;; and return best model by `classification-accuracy`
 
+(add-tap println)
 (def evaluation-results
   (ml/evaluate-pipelines
    pipe-fns