DEVELOPMENT... OpenML
Run
161133

Run 161133

Task 3818 (Supervised Classification) tae Uploaded 15-02-2015 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
0.7621
Per class
F measure
0.7604
Per class
Kappa
0.4672
KB relative information score
52.3023
Mean absolute error
0.2953
Mean prior absolute error
0.4522
Number of instances
151
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7596
Per class
Predictive accuracy
0.7616
Prior entropy
0.9308
Recall
0.7616
Per class
Relative absolute error
0.6529
Root mean prior squared error
0.4752
Root mean squared error
0.4315
Root relative squared error
0.9082
SciMark benchmark
933.8635
UserCPU time millis
40
UserCPU time millis training
40