Run
52280

Run 52280

Task 1748 (Learning Curve) tic-tac-toe Uploaded 07-11-2014 by Jan van Rijn
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.RealAdaBoost_MultilayerPerceptron(1)J. Friedman, T. Hastie, R. Tibshirani (2000). Additive Logistic Regression: a Statistical View of Boosting. Annals of Statistics. 95(2):337-407.
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.RealAdaBoost_MultilayerPerceptron(1)_P100
weka.RealAdaBoost_MultilayerPerceptron(1)_H1.0
weka.RealAdaBoost_MultilayerPerceptron(1)_S1
weka.RealAdaBoost_MultilayerPerceptron(1)_I10
weka.RealAdaBoost_MultilayerPerceptron(1)_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.

21 Evaluation measures

Area under ROC curve
0.9852 ± 0.0158
Per class
Build CPU time
13.5639
Build memory
2528179013.8667
F measure
0.978 ± 0.0127
Per class
Kappa
0.9513 ± 0.028
KB relative information score
0.9448 ± 0.0313
Mean absolute error
0.0242 ± 0.0138
Mean prior absolute error
0.453 ± 0.0013
Number of instances
958
Per class
OS information
[Oracle Corporation, 1.7.0_65, amd64, Linux, 3.5.0-54-generic]
Precision
0.9781 ± 0.0118
Per class
Predictive accuracy
0.9781 ± 0.0125
Prior entropy
0.931 ± 0.0039
Recall
0.9781 ± 0.0125
Per class
Relative absolute error
0.0535 ± 0.0304
Root mean prior squared error
0.4759 ± 0.0014
Root mean squared error
0.1483 ± 0.0402
Root relative squared error
0.3116 ± 0.0842
SciMark benchmark
1885.6155