Run
969

Run 969

Task 95 (Learning Curve) segment 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
0.9973 ± 0.0013
Per class
F measure
0.9588 ± 0.0123
Per class
Kappa
0.9519 ± 0.0143
KB relative information score
0.9414 ± 0.0096
Mean absolute error
0.0221 ± 0.0028
Mean prior absolute error
0.2449
Number of instances
23100
Per class
OS information
[ Oracle Corporation, 1.7.0_15, amd64, Linux, 3.5.0-27-generic ]
Precision
0.959 ± 0.012
Per class
Predictive accuracy
0.9588 ± 0.0123
Prior entropy
2.8074
Recall
0.9588 ± 0.0123
Per class
Relative absolute error
0.0902 ± 0.0112
Root mean prior squared error
0.3499
Root mean squared error
0.0951 ± 0.0107
Root relative squared error
0.2718 ± 0.0305
SciMark benchmark
882.7339