DEVELOPMENT... OpenML
Run
161048

Run 161048

Task 3732 (Supervised Classification) fri_c4_100_25 Uploaded 15-02-2015 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)_I160
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
0.7941
Per class
F measure
0.7404
Per class
Kappa
0.48
KB relative information score
46.2074
Mean absolute error
0.2677
Mean prior absolute error
0.4969
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
0.7432
Per class
Predictive accuracy
0.74
Prior entropy
0.9956
Recall
0.74
Per class
Relative absolute error
0.5387
Root mean prior squared error
0.4984
Root mean squared error
0.4881
Root relative squared error
0.9793
SciMark benchmark
938.4285
UserCPU time millis
80
UserCPU time millis testing
10
UserCPU time millis training
70