Run
9203163

Run 9203163

Task 3 (Supervised Classification) kr-vs-kp Uploaded 05-06-2018 by João Freitas
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Flow

sklearn.pipeline.Pipeline(onehotencoder=tpot.builtins.one_hot_encoder.OneHo tEncoder,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.Grad ientBoostingClassifier)(1)Automatically created scikit-learn flow.
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(13)_criterion"friedman_mse"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(13)_initnull
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(13)_learning_rate1.0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(13)_loss"deviance"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(13)_max_depth8
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(13)_max_features0.9500000000000001
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(13)_max_leaf_nodesnull
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(13)_min_impurity_decrease0.0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(13)_min_impurity_splitnull
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(13)_min_samples_leaf11
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(13)_min_samples_split16
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(13)_min_weight_fraction_leaf0.0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(13)_n_estimators100
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(13)_presort"auto"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(13)_random_state24833
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(13)_subsample1.0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(13)_verbose0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(13)_warm_startfalse
sklearn.pipeline.Pipeline(onehotencoder=tpot.builtins.one_hot_encoder.OneHotEncoder,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(1)_memorynull
tpot.builtins.one_hot_encoder.OneHotEncoder(1)_categorical_features[true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true]
tpot.builtins.one_hot_encoder.OneHotEncoder(1)_dtype{"oml-python:serialized_object": "type", "value": "np.float"}
tpot.builtins.one_hot_encoder.OneHotEncoder(1)_minimum_fraction0.1
tpot.builtins.one_hot_encoder.OneHotEncoder(1)_sparsefalse
tpot.builtins.one_hot_encoder.OneHotEncoder(1)_threshold10

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.

15 Evaluation measures

Area under ROC curve
0.4999
Per class
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-150.7558 ± 0.6266
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.5221 ± 0.0009
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.499 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
3196
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.4778 ± 0.001
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9986
Cross-validation details (10-fold Crossvalidation)
Recall
0.4778 ± 0.001
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
1.0462 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4995 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.7201 ± 0.0057
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.4417 ± 0.0114
Cross-validation details (10-fold Crossvalidation)