Run
10559710

Run 10559710

Task 3 (Supervised Classification) kr-vs-kp Uploaded 21-10-2020 by Mohit Aggarwal
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Flow

mango.model_selection.search.MangoSearchCV(estimator=sklearn.linear_model._ logistic.LogisticRegression)(1)Mango Search CV
sklearn.linear_model._logistic.LogisticRegression(4)_C1.0
sklearn.linear_model._logistic.LogisticRegression(4)_class_weightnull
sklearn.linear_model._logistic.LogisticRegression(4)_dualfalse
sklearn.linear_model._logistic.LogisticRegression(4)_fit_intercepttrue
sklearn.linear_model._logistic.LogisticRegression(4)_intercept_scaling1
sklearn.linear_model._logistic.LogisticRegression(4)_l1_rationull
sklearn.linear_model._logistic.LogisticRegression(4)_max_iter1000
sklearn.linear_model._logistic.LogisticRegression(4)_multi_class"auto"
sklearn.linear_model._logistic.LogisticRegression(4)_n_jobsnull
sklearn.linear_model._logistic.LogisticRegression(4)_penalty"l2"
sklearn.linear_model._logistic.LogisticRegression(4)_random_state56565
sklearn.linear_model._logistic.LogisticRegression(4)_solver"lbfgs"
sklearn.linear_model._logistic.LogisticRegression(4)_tol0.0001
sklearn.linear_model._logistic.LogisticRegression(4)_verbose0
sklearn.linear_model._logistic.LogisticRegression(4)_warm_startfalse
mango.model_selection.search.MangoSearchCV(estimator=sklearn.linear_model._logistic.LogisticRegression)(1)_cvnull
mango.model_selection.search.MangoSearchCV(estimator=sklearn.linear_model._logistic.LogisticRegression)(1)_error_scoreNaN
mango.model_selection.search.MangoSearchCV(estimator=sklearn.linear_model._logistic.LogisticRegression)(1)_iid"deprecated"
mango.model_selection.search.MangoSearchCV(estimator=sklearn.linear_model._logistic.LogisticRegression)(1)_n_init1
mango.model_selection.search.MangoSearchCV(estimator=sklearn.linear_model._logistic.LogisticRegression)(1)_n_iter1
mango.model_selection.search.MangoSearchCV(estimator=sklearn.linear_model._logistic.LogisticRegression)(1)_n_jobs-1
mango.model_selection.search.MangoSearchCV(estimator=sklearn.linear_model._logistic.LogisticRegression)(1)_param_distributions{"C": {"oml-python:serialized_object": "rv_frozen", "value": {"dist": "scipy.stats._continuous_distns.uniform_gen", "a": 0.0, "b": 1.0, "args": [1, 100], "kwds": {}}}}
mango.model_selection.search.MangoSearchCV(estimator=sklearn.linear_model._logistic.LogisticRegression)(1)_pre_dispatch"2*n_jobs"
mango.model_selection.search.MangoSearchCV(estimator=sklearn.linear_model._logistic.LogisticRegression)(1)_random_state14849
mango.model_selection.search.MangoSearchCV(estimator=sklearn.linear_model._logistic.LogisticRegression)(1)_refittrue
mango.model_selection.search.MangoSearchCV(estimator=sklearn.linear_model._logistic.LogisticRegression)(1)_return_train_scorefalse
mango.model_selection.search.MangoSearchCV(estimator=sklearn.linear_model._logistic.LogisticRegression)(1)_scoringnull
mango.model_selection.search.MangoSearchCV(estimator=sklearn.linear_model._logistic.LogisticRegression)(1)_verbose0

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.

18 Evaluation measures

Area under ROC curve
0.9952 ± 0.0026
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9715 ± 0.0112
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.943 ± 0.0224
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.9104 ± 0.0194
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0483 ± 0.0095
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.499 ± 0
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.9715 ± 0.0112
Cross-validation details (10-fold Crossvalidation)
Number of instances
3196
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9716 ± 0.0111
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9715 ± 0.0112
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9986 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0969 ± 0.0191
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4995 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1548 ± 0.0237
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.31 ± 0.0474
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.9717 ± 0.0112
Cross-validation details (10-fold Crossvalidation)