DEVELOPMENT... OpenML
Run
159822

Run 159822

Task 3523 (Supervised Classification) tr23.wc Uploaded 13-02-2015 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)_I80
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
0.9691
Per class
F measure
0.9323
Per class
Kappa
0.8985
KB relative information score
182.1149
Mean absolute error
0.0246
Mean prior absolute error
0.2385
Number of instances
204
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9433
Per class
Predictive accuracy
0.9265
Prior entropy
2.1253
Recall
0.9265
Per class
Relative absolute error
0.1033
Root mean prior squared error
0.3445
Root mean squared error
0.1527
Root relative squared error
0.4431
SciMark benchmark
941.7954
UserCPU time millis
501510
UserCPU time millis training
501510