DEVELOPMENT... OpenML
Run
173132

Run 173132

Task 3510 (Supervised Classification) JapaneseVowels Uploaded 21-02-2015 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
0.9971
Per class
F measure
0.9648
Per class
Kappa
0.9602
KB relative information score
9586.2994
Mean absolute error
0.0086
Mean prior absolute error
0.1962
Number of instances
9961
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9649
Per class
Predictive accuracy
0.9649
Prior entropy
3.1321
Recall
0.9649
Per class
Relative absolute error
0.0439
Root mean prior squared error
0.3132
Root mean squared error
0.0829
Root relative squared error
0.2646
SciMark benchmark
942.3168
UserCPU time millis
534310
UserCPU time millis testing
550
UserCPU time millis training
533760