From 58129e97fa46308554fe6f0ce58ddc8337fc676e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Ricardo=20Montan=CC=83ana?= Date: Mon, 21 Mar 2022 22:44:46 +0100 Subject: [PATCH 1/2] Add BaggingJ48 and Hedge results --- ...s_accuracy_BaggingJ48-SVMODT_Galgo_2022-03-17_12:00:00_0.json | 1 + results/results_accuracy_Hedge_Galgo_2022-03-17_12:00:00_0.json | 1 + 2 files changed, 2 insertions(+) create mode 100644 results/results_accuracy_BaggingJ48-SVMODT_Galgo_2022-03-17_12:00:00_0.json create mode 100644 results/results_accuracy_Hedge_Galgo_2022-03-17_12:00:00_0.json diff --git a/results/results_accuracy_BaggingJ48-SVMODT_Galgo_2022-03-17_12:00:00_0.json b/results/results_accuracy_BaggingJ48-SVMODT_Galgo_2022-03-17_12:00:00_0.json new file mode 100644 index 0000000..4a5e56e --- /dev/null +++ b/results/results_accuracy_BaggingJ48-SVMODT_Galgo_2022-03-17_12:00:00_0.json @@ -0,0 +1 @@ +{"score_name": "accuracy", "title": "Weka Bagging J48-SVMODT Ensemble execution", "model": "BaggingJ48SVMODT", 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newline at end of file From 5dbc067b2813c6721f8eb2a5e771cd8ac119cf82 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Ricardo=20Montan=CC=83ana?= Date: Mon, 21 Mar 2022 23:00:28 +0100 Subject: [PATCH 2/2] Add AdaBoostStree model --- .../best_results_accuracy_AdaBoostStree.json | 491 ++++++++++++++++++ src/Models.py | 11 +- 2 files changed, 500 insertions(+), 2 deletions(-) create mode 100644 results/best_results_accuracy_AdaBoostStree.json diff --git a/results/best_results_accuracy_AdaBoostStree.json b/results/best_results_accuracy_AdaBoostStree.json new file mode 100644 index 0000000..e8dd383 --- /dev/null +++ b/results/best_results_accuracy_AdaBoostStree.json @@ -0,0 +1,491 @@ +{ + "balance-scale": [ + 0.0, + { + "n_estimators": 100, + "algorithm": "SAMME", + "base_estimator__C": 10000.0, + "base_estimator__gamma": 0.1, + "base_estimator__kernel": "rbf", + "base_estimator__max_iter": 10000.0, + "base_estimator__multiclass_strategy": "ovr" + }, + "-program made-" + ], + "balloons": [ + 0.0, + 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"n_estimators": 100, + "algorithm": "SAMME", + "base_estimator__C": 0.1, + "base_estimator__max_iter": 10000.0, + "base_estimator__kernel": "liblinear", + "base_estimator__multiclass_strategy": "ovr" + }, + "-program made-" + ] +} diff --git a/src/Models.py b/src/Models.py index 5b12155..ef5ab72 100644 --- a/src/Models.py +++ b/src/Models.py @@ -1,6 +1,10 @@ from statistics import mean from sklearn.tree import DecisionTreeClassifier, ExtraTreeClassifier -from sklearn.ensemble import RandomForestClassifier, BaggingClassifier +from sklearn.ensemble import ( + RandomForestClassifier, + BaggingClassifier, + AdaBoostClassifier, +) from sklearn.svm import SVC from stree import Stree from wodt import Wodt @@ -28,6 +32,9 @@ class Models: if name == "BaggingWodt": clf = Wodt(random_state=random_state) return BaggingClassifier(base_estimator=clf) + if name == "AdaBoostStree": + clf = Stree(random_state=random_state) + return AdaBoostClassifier(base_estimator=clf) if name == "RandomForest": return RandomForestClassifier() msg = f"No model recognized {name}" @@ -47,7 +54,7 @@ class Models: nodes = 0 leaves = result.get_n_leaves() depth = 0 - elif name.startswith("Bagging"): + elif name.startswith("Bagging") or name.startswith("AdaBoost"): if hasattr(result.base_estimator_, "nodes_leaves"): nodes, leaves = list( zip(*[x.nodes_leaves() for x in result.estimators_])