Run
157

Run 157

Task 79 (Learning Curve) mfeat-pixel Uploaded 07-04-2014 by Jan van Rijn
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Flow

weka.LogitBoost_DecisionStump(1)J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
weka.LogitBoost_DecisionStump(1)_F0
weka.LogitBoost_DecisionStump(1)_H1.0
weka.LogitBoost_DecisionStump(1)_I10
weka.LogitBoost_DecisionStump(1)_L-1.7976931348623157E308
weka.LogitBoost_DecisionStump(1)_P100
weka.LogitBoost_DecisionStump(1)_R1
weka.LogitBoost_DecisionStump(1)_S1
weka.LogitBoost_DecisionStump(1)_Wweka.classifiers.trees.DecisionStump

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

19 Evaluation measures

Area under ROC curve
0.9937 ± 0.0026
Per class
F measure
0.9218 ± 0.0182
Per class
Kappa
0.9131 ± 0.0202
KB relative information score
0.8973 ± 0.0135
Mean absolute error
0.0291 ± 0.003
Mean prior absolute error
0.18
Number of instances
20000
Per class
OS information
[ Oracle Corporation, 1.7.0_51, amd64, Linux, 3.7.10-1.28-desktop ]
Precision
0.9223 ± 0.0173
Per class
Predictive accuracy
0.9218 ± 0.0182
Prior entropy
3.3219
Recall
0.9218 ± 0.0182
Per class
Relative absolute error
0.1614 ± 0.0169
Root mean prior squared error
0.3
Root mean squared error
0.1093 ± 0.0093
Root relative squared error
0.3644 ± 0.0311
SciMark benchmark
1955.4963