DEVELOPMENT... OpenML
Run
159336

Run 159336

Task 3708 (Supervised Classification) house_8L Uploaded 12-02-2015 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)_I40
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
0.9349
Per class
F measure
0.8747
Per class
Kappa
0.695
KB relative information score
13470.6055
Mean absolute error
0.1715
Mean prior absolute error
0.4168
Number of instances
22784
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8747
Per class
Predictive accuracy
0.8769
Prior entropy
0.8764
Recall
0.8769
Per class
Relative absolute error
0.4116
Root mean prior squared error
0.4565
Root mean squared error
0.2959
Root relative squared error
0.6483
SciMark benchmark
945.6434
UserCPU time millis
2820
UserCPU time millis testing
20
UserCPU time millis training
2800