Run
4495

Run 4495

Task 115 (Supervised Classification) diabetes Uploaded 18-10-2024 by Jan van Rijn
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Flow

weka.classifiers.meta.Bagging(weka.classifiers.functions.SMO(weka.classifie rs.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic)) (1)Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
weka.classifiers.functions.Logistic(1)_C["false"]
weka.classifiers.functions.Logistic(1)_S["false"]
weka.classifiers.functions.Logistic(1)_R["1.0E-8"]
weka.classifiers.functions.Logistic(1)_M["-1"]
weka.classifiers.functions.Logistic(1)_output-debug-info["false"]
weka.classifiers.functions.Logistic(1)_-do-not-check-capabilities["false"]
weka.classifiers.functions.Logistic(1)_num-decimal-places["4"]
weka.classifiers.meta.Bagging(weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic))(1)_P["7"]
weka.classifiers.meta.Bagging(weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic))(1)_O["false"]
weka.classifiers.meta.Bagging(weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic))(1)_store-out-of-bag-predictions["false"]
weka.classifiers.meta.Bagging(weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic))(1)_output-out-of-bag-complexity-statistics["false"]
weka.classifiers.meta.Bagging(weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic))(1)_represent-copies-using-weights["false"]
weka.classifiers.meta.Bagging(weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic))(1)_print["false"]
weka.classifiers.meta.Bagging(weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic))(1)_S["1"]
weka.classifiers.meta.Bagging(weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic))(1)_num-slots["1"]
weka.classifiers.meta.Bagging(weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic))(1)_I["2"]
weka.classifiers.meta.Bagging(weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic))(1)_W["weka.classifiers.functions.SMO"]
weka.classifiers.meta.Bagging(weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic))(1)_output-debug-info["false"]
weka.classifiers.meta.Bagging(weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic))(1)_-do-not-check-capabilities["false"]
weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic)(1)_no-checks["false"]
weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic)(1)_C["0.123"]
weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic)(1)_N["0"]
weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic)(1)_L["0.001"]
weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic)(1)_P["1.0E-12"]
weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic)(1)_M["false"]
weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic)(1)_V["-1"]
weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic)(1)_W["1"]
weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic)(1)_K["weka.classifiers.functions.supportVector.PolyKernel"]
weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic)(1)_calibrator["weka.classifiers.functions.Logistic"]
weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic)(1)_output-debug-info["false"]
weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic)(1)_-do-not-check-capabilities["false"]
weka.classifiers.functions.supportVector.PolyKernel(1)_E["3.0"]
weka.classifiers.functions.supportVector.PolyKernel(1)_L["false"]
weka.classifiers.functions.supportVector.PolyKernel(1)_C["250007"]
weka.classifiers.functions.supportVector.PolyKernel(1)_output-debug-info["false"]

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.

19 Evaluation measures

0.6912 ± 0.0402
Per class
0.6422 ± 0.0523
Per class
0.2188 ± 0.1025
0.3653 ± 0.0561
0.278 ± 0.0243
0.4545 ± 0.0011
0.7083 ± 0.03
768
Per class
['Eclipse Adoptium', '17.0.7', 'x86_64', 'Mac OS X', '12.5.1']
0.7511 ± 0.0483
Per class
0.7083 ± 0.03
0.9331 ± 0.0032
0.6117 ± 0.0533
0.4766 ± 0.0011
0.4811 ± 0.025
1.0093 ± 0.0521
0.5899 ± 0.0445