DEVELOPMENT... OpenML
Run
172749

Run 172749

Task 3501 (Supervised Classification) white-clover 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
0.8265
Per class
F measure
0.7249
Per class
Kappa
0.4834
KB relative information score
25.7697
Mean absolute error
0.1527
Mean prior absolute error
0.2721
Number of instances
63
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.722
Per class
Predictive accuracy
0.7302
Prior entropy
1.4097
Recall
0.7302
Per class
Relative absolute error
0.5612
Root mean prior squared error
0.3647
Root mean squared error
0.3498
Root relative squared error
0.9592
SciMark benchmark
917.4321
UserCPU time millis
1120
UserCPU time millis training
1120