Run
10229150

Run 10229150

Task 10101 (Supervised Classification) blood-transfusion-service-center Uploaded 09-07-2019 by Jan Ernsting
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Flow

sklearn.pipeline.Pipeline(pca=sklearn.preprocessing.data.StandardScaler,bin arizer=sklearn.preprocessing.data.PolynomialFeatures,clf=sklearn.svm.classe s.LinearSVC)(1)Automatically created scikit-learn flow.
sklearn.svm.classes.LinearSVC(10)_C1.0
sklearn.svm.classes.LinearSVC(10)_class_weightnull
sklearn.svm.classes.LinearSVC(10)_dualtrue
sklearn.svm.classes.LinearSVC(10)_fit_intercepttrue
sklearn.svm.classes.LinearSVC(10)_intercept_scaling1
sklearn.svm.classes.LinearSVC(10)_loss"squared_hinge"
sklearn.svm.classes.LinearSVC(10)_max_iter1000
sklearn.svm.classes.LinearSVC(10)_multi_class"ovr"
sklearn.svm.classes.LinearSVC(10)_penalty"l2"
sklearn.svm.classes.LinearSVC(10)_random_state43695
sklearn.svm.classes.LinearSVC(10)_tol0.0001
sklearn.svm.classes.LinearSVC(10)_verbose0
sklearn.preprocessing.data.StandardScaler(29)_copytrue
sklearn.preprocessing.data.StandardScaler(29)_with_meantrue
sklearn.preprocessing.data.StandardScaler(29)_with_stdtrue
sklearn.pipeline.Pipeline(pca=sklearn.preprocessing.data.StandardScaler,binarizer=sklearn.preprocessing.data.PolynomialFeatures,clf=sklearn.svm.classes.LinearSVC)(1)_memorynull
sklearn.pipeline.Pipeline(pca=sklearn.preprocessing.data.StandardScaler,binarizer=sklearn.preprocessing.data.PolynomialFeatures,clf=sklearn.svm.classes.LinearSVC)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "pca", "step_name": "pca"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "binarizer", "step_name": "binarizer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "clf", "step_name": "clf"}}]
sklearn.pipeline.Pipeline(pca=sklearn.preprocessing.data.StandardScaler,binarizer=sklearn.preprocessing.data.PolynomialFeatures,clf=sklearn.svm.classes.LinearSVC)(1)_verbosefalse
sklearn.preprocessing.data.PolynomialFeatures(5)_degree2
sklearn.preprocessing.data.PolynomialFeatures(5)_include_biastrue
sklearn.preprocessing.data.PolynomialFeatures(5)_interaction_onlyfalse
sklearn.preprocessing.data.PolynomialFeatures(5)_order"C"

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.

17 Evaluation measures

Area under ROC curve
0.5939 ± 0.0593
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7453 ± 0.0473
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2427 ± 0.1397
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.3394 ± 0.1041
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2126 ± 0.0339
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.363 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
Number of instances
748
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.765 ± 0.059
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7874 ± 0.0339
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.7916 ± 0.0072
Cross-validation details (10-fold Crossvalidation)
Recall
0.7874 ± 0.0339
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5855 ± 0.0926
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4258 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.461 ± 0.0371
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0827 ± 0.0856
Cross-validation details (10-fold Crossvalidation)