DEVELOPMENT... OpenML
Run
159975

Run 159975

Task 3592 (Supervised Classification) fri_c2_100_5 Uploaded 13-02-2015 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)_I80
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
0.8967
Per class
F measure
0.8296
Per class
Kappa
0.6444
KB relative information score
60.6026
Mean absolute error
0.1902
Mean prior absolute error
0.4804
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
0.8294
Per class
Predictive accuracy
0.83
Prior entropy
0.9721
Recall
0.83
Per class
Relative absolute error
0.396
Root mean prior squared error
0.4899
Root mean squared error
0.3784
Root relative squared error
0.7724
SciMark benchmark
924.6116
UserCPU time millis
10
UserCPU time millis training
10