DEVELOPMENT... OpenML
Run
159382

Run 159382

Task 3774 (Supervised Classification) fri_c2_250_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
0.9463
Per class
F measure
0.8755
Per class
Kappa
0.7466
KB relative information score
170.6819
Mean absolute error
0.1636
Mean prior absolute error
0.4929
Number of instances
250
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8764
Per class
Predictive accuracy
0.876
Prior entropy
0.9898
Recall
0.876
Per class
Relative absolute error
0.3318
Root mean prior squared error
0.4964
Root mean squared error
0.3015
Root relative squared error
0.6075
SciMark benchmark
924.6116
UserCPU time millis
30
UserCPU time millis testing
10
UserCPU time millis training
20