DEVELOPMENT... OpenML
Run
158282

Run 158282

Task 3907 (Supervised Classification) mc1 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
0.9363
Per class
F measure
0.9928
Per class
Kappa
0.3979
KB relative information score
-26904.9045
Mean absolute error
0.0109
Mean prior absolute error
0.0144
Number of instances
9466
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9934
Per class
Predictive accuracy
0.9943
Prior entropy
0.0622
Recall
0.9943
Per class
Relative absolute error
0.7586
Root mean prior squared error
0.0845
Root mean squared error
0.0741
Root relative squared error
0.8773
SciMark benchmark
945.6434
UserCPU time millis
1580
UserCPU time millis testing
10
UserCPU time millis training
1570