DEVELOPMENT... OpenML
Run
169941

Run 169941

Task 38 (Supervised Classification) ecoli 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
0.9449
Per class
F measure
0.8526
Per class
Kappa
0.8031
KB relative information score
258.4254
Mean absolute error
0.0373
Mean prior absolute error
0.1828
Number of instances
336
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8489
Per class
Predictive accuracy
0.8571
Prior entropy
2.2353
Recall
0.8571
Per class
Relative absolute error
0.2038
Root mean prior squared error
0.3016
Root mean squared error
0.1867
Root relative squared error
0.6188
SciMark benchmark
938.2848
UserCPU time millis
10020
UserCPU time millis testing
20
UserCPU time millis training
10000