DEVELOPMENT... OpenML
Run
159322

Run 159322

Task 3701 (Supervised Classification) sleuth_case1102 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
0.3632
Per class
F measure
0.3796
Per class
Kappa
-0.2615
KB relative information score
-6.8796
Mean absolute error
0.5861
Mean prior absolute error
0.4935
Number of instances
34
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.3775
Per class
Predictive accuracy
0.3824
Prior entropy
0.9911
Recall
0.3824
Per class
Relative absolute error
1.1878
Root mean prior squared error
0.4965
Root mean squared error
0.7004
Root relative squared error
1.4106
SciMark benchmark
945.6434
UserCPU time millis
10
UserCPU time millis testing
10