DEVELOPMENT... OpenML
Run
157236

Run 157236

Task 3898 (Supervised Classification) kc1-top5 Uploaded 11-02-2015 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)_I10
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
0.7304
Per class
F measure
0.9158
Per class
Kappa
0.1163
KB relative information score
-26.3081
Mean absolute error
0.0871
Mean prior absolute error
0.1096
Number of instances
145
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9086
Per class
Predictive accuracy
0.9241
Prior entropy
0.3323
Recall
0.9241
Per class
Relative absolute error
0.7943
Root mean prior squared error
0.2284
Root mean squared error
0.2655
Root relative squared error
1.1626
SciMark benchmark
931.2336
UserCPU time millis
20
UserCPU time millis training
20