DEVELOPMENT... OpenML
Run
159287

Run 159287

Task 3658 (Supervised Classification) fri_c3_250_10 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)_I40
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
0.969
Per class
F measure
0.9078
Per class
Kappa
0.8142
KB relative information score
185.9693
Mean absolute error
0.1348
Mean prior absolute error
0.4968
Number of instances
250
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9084
Per class
Predictive accuracy
0.908
Prior entropy
0.9955
Recall
0.908
Per class
Relative absolute error
0.2714
Root mean prior squared error
0.4984
Root mean squared error
0.2656
Root relative squared error
0.533
SciMark benchmark
924.6116
UserCPU time millis
20
UserCPU time millis training
20