DEVELOPMENT... OpenML
Run
172673

Run 172673

Task 29 (Supervised Classification) credit-approval Uploaded 20-02-2015 by Felicia West
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.MultiBoostAB_MultilayerPerceptron(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.MultilayerPerceptron(2)_E20
weka.MultilayerPerceptron(2)_Ha
weka.MultilayerPerceptron(2)_L0.3
weka.MultilayerPerceptron(2)_M0.2
weka.MultilayerPerceptron(2)_N500
weka.MultilayerPerceptron(2)_S0
weka.MultilayerPerceptron(2)_V0
weka.MultiBoostAB_MultilayerPerceptron(2)_C3
weka.MultiBoostAB_MultilayerPerceptron(2)_P100
weka.MultiBoostAB_MultilayerPerceptron(2)_S1
weka.MultiBoostAB_MultilayerPerceptron(2)_I10
weka.MultiBoostAB_MultilayerPerceptron(2)_Wweka.classifiers.functions.MultilayerPerceptron

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

model
Model readable

A human-readable description of the model that was built.

model
Model serialized

A serialized description of the model that can be read by the tool that generated it.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

22 Evaluation measures

Area under ROC curve
0.8877
Per class
F measure
0.8406
Per class
Kappa
0.6772
KB relative information score
460.9029
Mean absolute error
0.164
Mean prior absolute error
0.494
Number of instances
690
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8406
Per class
Predictive accuracy
0.8406
Prior entropy
0.9913
Recall
0.8406
Per class
Relative absolute error
0.3321
Root mean prior squared error
0.497
Root mean squared error
0.3827
Root relative squared error
0.7701
SciMark benchmark
921.8984
UserCPU time millis
90620
UserCPU time millis testing
100
UserCPU time millis training
90520