DEVELOPMENT... OpenML
Run
157362

Run 157362

Task 16 (Supervised Classification) mfeat-karhunen 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)_I20
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
0.9945
Per class
F measure
0.9245
Per class
Kappa
0.9161
KB relative information score
1823.7039
Mean absolute error
0.0237
Mean prior absolute error
0.18
Number of instances
2000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9247
Per class
Predictive accuracy
0.9245
Prior entropy
3.3219
Recall
0.9245
Per class
Relative absolute error
0.1319
Root mean prior squared error
0.3
Root mean squared error
0.1071
Root relative squared error
0.3569
SciMark benchmark
933.8635
UserCPU time millis
8110
UserCPU time millis training
8110