DEVELOPMENT... OpenML
Run
161120

Run 161120

Task 3804 (Supervised Classification) lowbwt Uploaded 15-02-2015 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)_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
0.903
Per class
F measure
0.8197
Per class
Kappa
0.6383
KB relative information score
117.4677
Mean absolute error
0.1914
Mean prior absolute error
0.4989
Number of instances
189
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8209
Per class
Predictive accuracy
0.8201
Prior entropy
0.9984
Recall
0.8201
Per class
Relative absolute error
0.3836
Root mean prior squared error
0.4994
Root mean squared error
0.3679
Root relative squared error
0.7366
SciMark benchmark
933.8635
UserCPU time millis
30
UserCPU time millis training
30