DEVELOPMENT... OpenML
Run
163173

Run 163173

Task 3524 (Supervised Classification) fbis.wc Uploaded 16-02-2015 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)_I160
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
0.982
Per class
F measure
0.8669
Per class
Kappa
0.8531
KB relative information score
2114.3616
Mean absolute error
0.0162
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
0.8663
Per class
Predictive accuracy
0.8697
Prior entropy
3.5848
Recall
0.8697
Per class
Relative absolute error
0.1543
Root mean prior squared error
0.2288
Root mean squared error
0.1162
Root relative squared error
0.5078
SciMark benchmark
911.0478
UserCPU time millis
11903910
UserCPU time millis testing
10
UserCPU time millis training
11903900