DEVELOPMENT... OpenML
Run
160206

Run 160206

Task 3857 (Supervised Classification) vehicle Uploaded 13-02-2015 by Felicia West
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


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)_I80
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
0.9957
Per class
F measure
0.9799
Per class
Kappa
0.9474
KB relative information score
777.2953
Mean absolute error
0.0309
Mean prior absolute error
0.3828
Number of instances
846
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9799
Per class
Predictive accuracy
0.9799
Prior entropy
0.8241
Recall
0.9799
Per class
Relative absolute error
0.0808
Root mean prior squared error
0.4374
Root mean squared error
0.1308
Root relative squared error
0.2991
SciMark benchmark
924.6116
UserCPU time millis
240
UserCPU time millis training
240