DEVELOPMENT... OpenML
Run
157484

Run 157484

Task 2072 (Supervised Classification) covertype 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
0.8369
Per class
F measure
0.67
Per class
Kappa
0.4944
KB relative information score
48264.2201
Mean absolute error
0.126
Mean prior absolute error
0.1853
Number of instances
110393
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.6852
Per class
Predictive accuracy
0.687
Prior entropy
1.8698
Recall
0.687
Per class
Relative absolute error
0.6803
Root mean prior squared error
0.3044
Root mean squared error
0.2511
Root relative squared error
0.825
SciMark benchmark
943.2817
UserCPU time millis
243080
UserCPU time millis testing
180
UserCPU time millis training
242900