DEVELOPMENT... OpenML
Run
159265

Run 159265

Task 3634 (Supervised Classification) fri_c3_100_25 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
0.8069
Per class
F measure
0.7103
Per class
Kappa
0.4153
KB relative information score
41.4979
Mean absolute error
0.2917
Mean prior absolute error
0.4951
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
0.7107
Per class
Predictive accuracy
0.71
Prior entropy
0.9931
Recall
0.71
Per class
Relative absolute error
0.5891
Root mean prior squared error
0.4975
Root mean squared error
0.4552
Root relative squared error
0.915
SciMark benchmark
924.6116
UserCPU time millis
30
UserCPU time millis testing
10
UserCPU time millis training
20