Run
14820

Run 14820

Task 1735 (Learning Curve) segment Uploaded 03-06-2014 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
0.9975 ± 0.0012
Per class
F measure
0.9585 ± 0.0124
Per class
Kappa
0.9515 ± 0.0145
KB relative information score
0.9413 ± 0.0105
Mean absolute error
0.0222 ± 0.0031
Mean prior absolute error
0.2449
Number of instances
2310
Per class
OS information
[ Oracle Corporation, 1.7.0_15, amd64, Linux, 3.5.0-27-generic ]
Precision
0.9589 ± 0.0122
Per class
Predictive accuracy
0.9584 ± 0.0124
Prior entropy
2.8074
Recall
0.9584 ± 0.0124
Per class
Relative absolute error
0.0906 ± 0.0126
Root mean prior squared error
0.3499
Root mean squared error
0.0947 ± 0.0116
Root relative squared error
0.2707 ± 0.0332
SciMark benchmark
869.5106