DEVELOPMENT... OpenML
Run
158701

Run 158701

Task 3524 (Supervised Classification) fbis.wc Uploaded 12-02-2015 by Felicia West
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Flow

weka.LogitBoost_DecisionStump(2)J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
weka.LogitBoost_DecisionStump(2)_E1
weka.LogitBoost_DecisionStump(2)_H1.0
weka.LogitBoost_DecisionStump(2)_I20
weka.LogitBoost_DecisionStump(2)_L-1.7976931348623157E308
weka.LogitBoost_DecisionStump(2)_O1
weka.LogitBoost_DecisionStump(2)_P100
weka.LogitBoost_DecisionStump(2)_S1
weka.LogitBoost_DecisionStump(2)_Wweka.classifiers.trees.DecisionStump
weka.LogitBoost_DecisionStump(2)_Z3.0

Result files

xml
Description

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

model
Model readable

A human-readable description of the model that was built.

model
Model serialized

A serialized description of the model that can be read by the tool that generated it.

arff
Predictions

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

22 Evaluation measures

Area under ROC curve
0.9858
Per class
F measure
0.8471
Per class
Kappa
0.8306
KB relative information score
2072.8428
Mean absolute error
0.0229
Mean prior absolute error
0.1047
Number of instances
2463
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8465
Per class
Predictive accuracy
0.8498
Prior entropy
3.5848
Recall
0.8498
Per class
Relative absolute error
0.219
Root mean prior squared error
0.2288
Root mean squared error
0.1149
Root relative squared error
0.502
SciMark benchmark
897.6255
UserCPU time millis
1558440
UserCPU time millis testing
10
UserCPU time millis training
1558430