DEVELOPMENT... OpenML
Run
156950

Run 156950

Task 3612 (Supervised Classification) fri_c1_250_25 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)_I10
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
0.8856
Per class
F measure
0.8033
Per class
Kappa
0.5973
KB relative information score
114.6702
Mean absolute error
0.2798
Mean prior absolute error
0.4897
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
0.8033
Per class
Predictive accuracy
0.804
Prior entropy
0.9852
Recall
0.804
Per class
Relative absolute error
0.5714
Root mean prior squared error
0.4948
Root mean squared error
0.3658
Root relative squared error
0.7394
SciMark benchmark
929.566
UserCPU time millis
20
UserCPU time millis training
20