DEVELOPMENT... OpenML
Run
161013

Run 161013

Task 3688 (Supervised Classification) houses 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
0.9986
Per class
F measure
0.9815
Per class
Kappa
0.9623
KB relative information score
19556.182
Mean absolute error
0.0274
Mean prior absolute error
0.4907
Number of instances
20640
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9815
Per class
Predictive accuracy
0.9815
Prior entropy
0.9866
Recall
0.9815
Per class
Relative absolute error
0.0557
Root mean prior squared error
0.4953
Root mean squared error
0.1178
Root relative squared error
0.2377
SciMark benchmark
938.4285
UserCPU time millis
7950
UserCPU time millis testing
10
UserCPU time millis training
7940