DEVELOPMENT... OpenML
Run
158184

Run 158184

Task 3821 (Supervised Classification) segment 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
0.9996
Per class
F measure
0.9957
Per class
Kappa
0.9823
KB relative information score
2220.7312
Mean absolute error
0.0091
Mean prior absolute error
0.2451
Number of instances
2310
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9957
Per class
Predictive accuracy
0.9957
Prior entropy
0.5925
Recall
0.9957
Per class
Relative absolute error
0.037
Root mean prior squared error
0.3499
Root mean squared error
0.0566
Root relative squared error
0.1619
SciMark benchmark
947.9494
UserCPU time millis
210
UserCPU time millis testing
10
UserCPU time millis training
200