DEVELOPMENT... OpenML
Run
161198

Run 161198

Task 3882 (Supervised Classification) pendigits 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
0.9992
Per class
F measure
0.9963
Per class
Kappa
0.98
KB relative information score
10519.8761
Mean absolute error
0.0063
Mean prior absolute error
0.1865
Number of instances
10992
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9963
Per class
Predictive accuracy
0.9963
Prior entropy
0.482
Recall
0.9963
Per class
Relative absolute error
0.0339
Root mean prior squared error
0.3054
Root mean squared error
0.0565
Root relative squared error
0.185
SciMark benchmark
936.6206
UserCPU time millis
5850
UserCPU time millis testing
10
UserCPU time millis training
5840