DEVELOPMENT... OpenML
Run
159253

Run 159253

Task 3620 (Supervised Classification) fri_c0_100_5 Uploaded 12-02-2015 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)_I40
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
0.9275
Per class
F measure
0.849
Per class
Kappa
0.6956
KB relative information score
63.8043
Mean absolute error
0.183
Mean prior absolute error
0.4969
Number of instances
100
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8524
Per class
Predictive accuracy
0.85
Prior entropy
0.9956
Recall
0.85
Per class
Relative absolute error
0.3683
Root mean prior squared error
0.4984
Root mean squared error
0.3579
Root relative squared error
0.7182
SciMark benchmark
924.6116
UserCPU time millis
10
UserCPU time millis training
10