Run
1896

Run 1896

Task 97 (Learning Curve) ecoli Uploaded 23-04-2014 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
0.9606 ± 0.0213
Per class
F measure
0.829 ± 0.0614
Per class
Kappa
0.7713 ± 0.0826
KB relative information score
0.7462 ± 0.0751
Mean absolute error
0.053 ± 0.0112
Mean prior absolute error
0.1828 ± 0.0012
Number of instances
3360
Per class
OS information
[ Oracle Corporation, 1.7.0_15, amd64, Linux, 3.5.0-27-generic ]
Precision
0.8246 ± 0.0625
Per class
Predictive accuracy
0.8348 ± 0.0599
Prior entropy
2.1906 ± 0.0868
Recall
0.8348 ± 0.0599
Per class
Relative absolute error
0.29 ± 0.0605
Root mean prior squared error
0.3016 ± 0.0021
Root mean squared error
0.1759 ± 0.0296
Root relative squared error
0.5831 ± 0.0964
SciMark benchmark
833.245