DEVELOPMENT... OpenML
Run
161136

Run 161136

Task 3820 (Supervised Classification) braziltourism Uploaded 15-02-2015 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)_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
0.6778
Per class
F measure
0.7453
Per class
Kappa
0.2372
KB relative information score
44.7747
Mean absolute error
0.2882
Mean prior absolute error
0.3529
Number of instances
412
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7374
Per class
Predictive accuracy
0.7646
Prior entropy
0.7771
Recall
0.7646
Per class
Relative absolute error
0.8167
Root mean prior squared error
0.4196
Root mean squared error
0.4218
Root relative squared error
1.0052
SciMark benchmark
933.8635
UserCPU time millis
110
UserCPU time millis training
110