Run
2300439

Run 2300439

Task 49 (Supervised Classification) tic-tac-toe Uploaded 22-05-2017 by Jeroen van Hoof
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Flow

optimus.model_optimizer.ModelOptimizer(estimator=sklearn.linear_model.logis tic.LogisticRegression)(3)Automatically created scikit-learn flow.
sklearn.linear_model.logistic.LogisticRegression(3)_C1.0
sklearn.linear_model.logistic.LogisticRegression(3)_class_weightnull
sklearn.linear_model.logistic.LogisticRegression(3)_dualfalse
sklearn.linear_model.logistic.LogisticRegression(3)_fit_intercepttrue
sklearn.linear_model.logistic.LogisticRegression(3)_intercept_scaling1
sklearn.linear_model.logistic.LogisticRegression(3)_max_iter100
sklearn.linear_model.logistic.LogisticRegression(3)_multi_class"ovr"
sklearn.linear_model.logistic.LogisticRegression(3)_n_jobs-1
sklearn.linear_model.logistic.LogisticRegression(3)_penalty"l2"
sklearn.linear_model.logistic.LogisticRegression(3)_random_state6
sklearn.linear_model.logistic.LogisticRegression(3)_solver"liblinear"
sklearn.linear_model.logistic.LogisticRegression(3)_tol0.0001
sklearn.linear_model.logistic.LogisticRegression(3)_verbose0
sklearn.linear_model.logistic.LogisticRegression(3)_warm_startfalse
optimus.model_optimizer.ModelOptimizer(estimator=sklearn.linear_model.logistic.LogisticRegression)(3)_draw_samples100
optimus.model_optimizer.ModelOptimizer(estimator=sklearn.linear_model.logistic.LogisticRegression)(3)_encoded_params{"!@preprocessor": [null, ["sklearn.preprocessing.StandardScaler", {}]], "C": [0.0001, 0.001, 0.01, 0.1, 0.5, 1.0, 5.0, 10.0, 15.0, 20.0, 25.0], "dual": [true, false]}
optimus.model_optimizer.ModelOptimizer(estimator=sklearn.linear_model.logistic.LogisticRegression)(3)_estimator{"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": null}}
optimus.model_optimizer.ModelOptimizer(estimator=sklearn.linear_model.logistic.LogisticRegression)(3)_inner_cv3
optimus.model_optimizer.ModelOptimizer(estimator=sklearn.linear_model.logistic.LogisticRegression)(3)_max_eval_time120
optimus.model_optimizer.ModelOptimizer(estimator=sklearn.linear_model.logistic.LogisticRegression)(3)_scoring"accuracy"
optimus.model_optimizer.ModelOptimizer(estimator=sklearn.linear_model.logistic.LogisticRegression)(3)_timeout_score0
optimus.model_optimizer.ModelOptimizer(estimator=sklearn.linear_model.logistic.LogisticRegression)(3)_use_ei_per_secondfalse
optimus.model_optimizer.ModelOptimizer(estimator=sklearn.linear_model.logistic.LogisticRegression)(3)_verbosetrue

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.

arff
Trace

ARFF file with the trace of all hyperparameter settings tried during optimization, and their performance.

17 Evaluation measures

Area under ROC curve
0.6068
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6506
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2184
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-27.7875
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4537
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.453
Cross-validation details (10-fold Crossvalidation)
Number of instances
958
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.6924
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.6983
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9312
Cross-validation details (10-fold Crossvalidation)
Recall
0.6983
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
1.0015
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4759
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4738
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9956
Cross-validation details (10-fold Crossvalidation)