DEVELOPMENT... OpenML
Run
160876

Run 160876

Task 3564 (Supervised Classification) analcatdata_germangss 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
0.7341
Per class
F measure
0.419
Per class
Kappa
0.2267
KB relative information score
115.1384
Mean absolute error
0.3036
Mean prior absolute error
0.375
Number of instances
400
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.4184
Per class
Predictive accuracy
0.42
Prior entropy
2
Recall
0.42
Per class
Relative absolute error
0.8097
Root mean prior squared error
0.433
Root mean squared error
0.4127
Root relative squared error
0.953
SciMark benchmark
945.6434
UserCPU time millis
160
UserCPU time millis testing
10
UserCPU time millis training
150