Run
707

Run 707

Task 72 (Learning Curve) breast-cancer Uploaded 08-04-2014 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
0.643 ± 0.0978
Per class
F measure
0.6768 ± 0.0764
Per class
Kappa
0.195 ± 0.1792
KB relative information score
0.0913 ± 0.108
Mean absolute error
0.369 ± 0.0366
Mean prior absolute error
0.4183 ± 0.0065
Number of instances
2860
Per class
OS information
[ Sun Microsystems Inc., 1.6.0_30, amd64, Linux, 2.6.32-358.6.2.el6.x86_64 ]
Precision
0.6725 ± 0.0931
Per class
Predictive accuracy
0.7014 ± 0.0703
Prior entropy
0.8779 ± 0.0199
Recall
0.7014 ± 0.0703
Per class
Relative absolute error
0.882 ± 0.0843
Root mean prior squared error
0.457 ± 0.0071
Root mean squared error
0.4545 ± 0.039
Root relative squared error
0.9945 ± 0.0821
SciMark benchmark
910.4774