DEVELOPMENT... OpenML
Run
156955

Run 156955

Task 3617 (Supervised Classification) fri_c4_1000_10 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
0.9284
Per class
F measure
0.8399
Per class
Kappa
0.675
KB relative information score
528.6412
Mean absolute error
0.249
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
0.8399
Per class
Predictive accuracy
0.84
Prior entropy
0.9896
Recall
0.84
Per class
Relative absolute error
0.5053
Root mean prior squared error
0.4964
Root mean squared error
0.3301
Root relative squared error
0.6649
SciMark benchmark
931.2336
UserCPU time millis
20
UserCPU time millis training
20