DEVELOPMENT... OpenML
Run
159983

Run 159983

Task 3602 (Supervised Classification) visualizing_environmental Uploaded 13-02-2015 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)_I80
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
0.7214
Per class
F measure
0.6657
Per class
Kappa
0.3368
KB relative information score
33.3938
Mean absolute error
0.3522
Mean prior absolute error
0.499
Number of instances
111
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.6736
Per class
Predictive accuracy
0.6667
Prior entropy
0.9986
Recall
0.6667
Per class
Relative absolute error
0.7058
Root mean prior squared error
0.4995
Root mean squared error
0.4943
Root relative squared error
0.9896
SciMark benchmark
924.6116
UserCPU time millis
10
UserCPU time millis training
10