OpenML
160909

Run 160909

Task 3595 (Supervised Classification) visualizing_slope Uploaded 15-02-2015 by Joaquin Vanschoren
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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
0.9281
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9321
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.8578
Cross-validation details (10-fold Crossvalidation)
KB relative information score
37.412
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0684
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4753
Cross-validation details (10-fold Crossvalidation)
Number of instances
44
Per class
Cross-validation details (10-fold Crossvalidation)
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9335
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9318
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9656
Cross-validation details (10-fold Crossvalidation)
Recall
0.9318
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1439
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4869
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2611
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.5362
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
936.6206
UserCPU time millis
10
Cross-validation details (10-fold Crossvalidation)
UserCPU time millis testing
Cross-validation details (10-fold Crossvalidation)
UserCPU time millis training
10
Cross-validation details (10-fold Crossvalidation)