Run
10595189

Run 10595189

Task 7543 (Supervised Classification) diabetes Uploaded 03-12-2024 by Vitor Pina
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Flow

sklearn.ensemble._weight_boosting.AdaBoostClassifier(estimator=sklearn.tree ._classes.DecisionTreeClassifier)(2)An AdaBoost classifier. An AdaBoost [1]_ classifier is a meta-estimator that begins by fitting a classifier on the original dataset and then fits additional copies of the classifier on the same dataset but where the weights of incorrectly classified instances are adjusted such that subsequent classifiers focus more on difficult cases. This class implements the algorithm based on [2]_.
sklearn.tree._classes.DecisionTreeClassifier(50)_ccp_alpha0.0
sklearn.tree._classes.DecisionTreeClassifier(50)_class_weightnull
sklearn.tree._classes.DecisionTreeClassifier(50)_criterion"gini"
sklearn.tree._classes.DecisionTreeClassifier(50)_max_depth1
sklearn.tree._classes.DecisionTreeClassifier(50)_max_featuresnull
sklearn.tree._classes.DecisionTreeClassifier(50)_max_leaf_nodesnull
sklearn.tree._classes.DecisionTreeClassifier(50)_min_impurity_decrease0.0
sklearn.tree._classes.DecisionTreeClassifier(50)_min_samples_leaf1
sklearn.tree._classes.DecisionTreeClassifier(50)_min_samples_split2
sklearn.tree._classes.DecisionTreeClassifier(50)_min_weight_fraction_leaf0.0
sklearn.tree._classes.DecisionTreeClassifier(50)_monotonic_cstnull
sklearn.tree._classes.DecisionTreeClassifier(50)_random_state8211
sklearn.tree._classes.DecisionTreeClassifier(50)_splitter"best"
sklearn.ensemble._weight_boosting.AdaBoostClassifier(estimator=sklearn.tree._classes.DecisionTreeClassifier)(2)_algorithm"SAMME.R"
sklearn.ensemble._weight_boosting.AdaBoostClassifier(estimator=sklearn.tree._classes.DecisionTreeClassifier)(2)_learning_rate1.0
sklearn.ensemble._weight_boosting.AdaBoostClassifier(estimator=sklearn.tree._classes.DecisionTreeClassifier)(2)_n_estimators50
sklearn.ensemble._weight_boosting.AdaBoostClassifier(estimator=sklearn.tree._classes.DecisionTreeClassifier)(2)_random_state32737

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

18 Evaluation measures

Area under ROC curve
0.8276
Per class
Cross-validation details (10% Holdout set)
F measure
0.7383
Per class
Cross-validation details (10% Holdout set)
Kappa
0.4275
Cross-validation details (10% Holdout set)
KB relative information score
-0.1181
Cross-validation details (10% Holdout set)
Mean absolute error
0.4901
Cross-validation details (10% Holdout set)
Mean prior absolute error
0.4589
Cross-validation details (10% Holdout set)
Weighted recall
0.7431
Cross-validation details (10% Holdout set)
Number of instances
253
Per class
Cross-validation details (10% Holdout set)
Precision
0.7377
Per class
Cross-validation details (10% Holdout set)
Predictive accuracy
0.7431
Cross-validation details (10% Holdout set)
Prior entropy
0.9463
Cross-validation details (10% Holdout set)
Relative absolute error
1.0678
Cross-validation details (10% Holdout set)
Root mean prior squared error
0.4813
Cross-validation details (10% Holdout set)
Root mean squared error
0.4903
Cross-validation details (10% Holdout set)
Root relative squared error
1.0187
Cross-validation details (10% Holdout set)
Unweighted recall
0.7073
Cross-validation details (10% Holdout set)