DEVELOPMENT... OpenML
Run
160119

Run 160119

Task 3762 (Supervised Classification) analcatdata_negotiation 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
0.8855
Per class
F measure
0.7922
Per class
Kappa
0.4847
KB relative information score
43.1981
Mean absolute error
0.196
Mean prior absolute error
0.4075
Number of instances
92
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7912
Per class
Predictive accuracy
0.7935
Prior entropy
0.8651
Recall
0.7935
Per class
Relative absolute error
0.4809
Root mean prior squared error
0.4503
Root mean squared error
0.4123
Root relative squared error
0.9157
SciMark benchmark
924.6116
UserCPU time millis
10
UserCPU time millis training
10