DEVELOPMENT... OpenML
Run
161096

Run 161096

Task 3781 (Supervised Classification) fri_c4_250_50 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
0.8598
Per class
F measure
0.7791
Per class
Kappa
0.5546
KB relative information score
135.7347
Mean absolute error
0.2283
Mean prior absolute error
0.4968
Number of instances
250
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7802
Per class
Predictive accuracy
0.78
Prior entropy
0.9955
Recall
0.78
Per class
Relative absolute error
0.4595
Root mean prior squared error
0.4984
Root mean squared error
0.4276
Root relative squared error
0.8579
SciMark benchmark
933.8635
UserCPU time millis
550
UserCPU time millis training
550