DEVELOPMENT... OpenML
Run
157072

Run 157072

Task 3734 (Supervised Classification) fri_c1_500_5 Uploaded 11-02-2015 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)_I10
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
0.9003
Per class
F measure
0.8174
Per class
Kappa
0.6326
KB relative information score
252.4074
Mean absolute error
0.2614
Mean prior absolute error
0.4977
Number of instances
500
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8186
Per class
Predictive accuracy
0.818
Prior entropy
0.9967
Recall
0.818
Per class
Relative absolute error
0.5253
Root mean prior squared error
0.4988
Root mean squared error
0.3545
Root relative squared error
0.7106
SciMark benchmark
931.2336
UserCPU time millis
10
UserCPU time millis training
10