DEVELOPMENT... OpenML
Run
157001

Run 157001

Task 3662 (Supervised Classification) fri_c4_1000_50 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
0.9235
Per class
F measure
0.8572
Per class
Kappa
0.7094
KB relative information score
511.3136
Mean absolute error
0.2595
Mean prior absolute error
0.4928
Number of instances
1000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8585
Per class
Predictive accuracy
0.858
Prior entropy
0.9896
Recall
0.858
Per class
Relative absolute error
0.5266
Root mean prior squared error
0.4964
Root mean squared error
0.3355
Root relative squared error
0.6759
SciMark benchmark
929.566
UserCPU time millis
120
UserCPU time millis training
120