DEVELOPMENT... OpenML
Run
159297

Run 159297

Task 3947 (Supervised Classification) KDDCup99 Uploaded 12-02-2015 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)_I20
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
1
Per class
F measure
0.9997
Per class
Kappa
0.9995
KB relative information score
493231.5358
Mean absolute error
0.0001
Mean prior absolute error
0.0514
Number of instances
494020
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9997
Per class
Predictive accuracy
0.9997
Prior entropy
1.5581
Recall
0.9997
Per class
Relative absolute error
0.0012
Root mean prior squared error
0.1603
Root mean squared error
0.0048
Root relative squared error
0.0297
SciMark benchmark
945.6434
UserCPU time millis
3834000
UserCPU time millis testing
1950
UserCPU time millis training
3832050