Run
22048

Run 22048

Task 34 (Supervised Classification) postoperative-patient-data Uploaded 21-06-2014 by Joaquin Vanschoren
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Flow

weka.MultiBoostAB_MultilayerPerceptron(1)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.MultiBoostAB_MultilayerPerceptron(1)_C3
weka.MultiBoostAB_MultilayerPerceptron(1)_I40
weka.MultiBoostAB_MultilayerPerceptron(1)_P100
weka.MultiBoostAB_MultilayerPerceptron(1)_S1
weka.MultiBoostAB_MultilayerPerceptron(1)_Wweka.classifiers.functions.MultilayerPerceptron
weka.MultilayerPerceptron(1)_E20
weka.MultilayerPerceptron(1)_Ha
weka.MultilayerPerceptron(1)_L0.3
weka.MultilayerPerceptron(1)_M0.2
weka.MultilayerPerceptron(1)_N500
weka.MultilayerPerceptron(1)_S0
weka.MultilayerPerceptron(1)_V0

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

Area under ROC curve
0.5038
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.5451
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
-0.1325
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-5.4424
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.283
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2871
Cross-validation details (10-fold Crossvalidation)
Number of instances
90
Per class
Cross-validation details (10-fold Crossvalidation)
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.5184
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.5778
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.0305
Cross-validation details (10-fold Crossvalidation)
Recall
0.5778
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.986
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3755
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.5204
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.3859
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
919.5688[555.667624694253985.6547740150851466.84428098298696892.5570199707421697.120398816452]