DEVELOPMENT... OpenML
Run
166322

Run 166322

Task 59 (Supervised Classification) iris Uploaded 18-02-2015 by Felicia West
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Flow

weka.LogitBoost_DecisionStump(3)J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
weka.LogitBoost_DecisionStump(3)_P100
weka.LogitBoost_DecisionStump(3)_L-1.7976931348623157E308
weka.LogitBoost_DecisionStump(3)_H1.0
weka.LogitBoost_DecisionStump(3)_Z3.0
weka.LogitBoost_DecisionStump(3)_O1
weka.LogitBoost_DecisionStump(3)_E1
weka.LogitBoost_DecisionStump(3)_S1
weka.LogitBoost_DecisionStump(3)_I80
weka.LogitBoost_DecisionStump(3)_Wweka.classifiers.trees.DecisionStump

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
0.9669
Per class
F measure
0.9333
Per class
Kappa
0.9
KB relative information score
135.7807
Mean absolute error
0.0462
Mean prior absolute error
0.4444
Number of instances
150
Per class
OS information
[Oracle Corporation, 1.7.0_04, x86_64, Mac OS X, 10.10.2]
Precision
0.9333
Per class
Predictive accuracy
0.9333
Prior entropy
1.585
Recall
0.9333
Per class
Relative absolute error
0.1041
Root mean prior squared error
0.4714
Root mean squared error
0.2071
Root relative squared error
0.4393
SciMark benchmark
1289.6995
UserCPU time millis
35.34
UserCPU time millis testing
0.567
UserCPU time millis training
34.773