DEVELOPMENT... OpenML
Run
169782

Run 169782

Task 4 (Supervised Classification) labor Uploaded 20-02-2015 by Felicia West
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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
0.9716
Per class
F measure
0.9305
Per class
Kappa
0.8494
KB relative information score
44.9893
Mean absolute error
0.0945
Mean prior absolute error
0.457
Number of instances
57
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9336
Per class
Predictive accuracy
0.9298
Prior entropy
0.9393
Recall
0.9298
Per class
Relative absolute error
0.2068
Root mean prior squared error
0.4773
Root mean squared error
0.2458
Root relative squared error
0.5151
SciMark benchmark
889.9795
UserCPU time millis
370
UserCPU time millis training
370