DEVELOPMENT... OpenML
Run
151547

Run 151547

Task 3706 (Supervised Classification) stock Uploaded 09-02-2015 by Felicia West
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.IterativeClassifierOptimizer_LogitBoost_DecisionStump(1)Weka implementation of IterativeClassifierOptimizer
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
weka.IterativeClassifierOptimizer_LogitBoost_DecisionStump(1)_L50
weka.IterativeClassifierOptimizer_LogitBoost_DecisionStump(1)_P1
weka.IterativeClassifierOptimizer_LogitBoost_DecisionStump(1)_E1
weka.IterativeClassifierOptimizer_LogitBoost_DecisionStump(1)_I1
weka.IterativeClassifierOptimizer_LogitBoost_DecisionStump(1)_F10
weka.IterativeClassifierOptimizer_LogitBoost_DecisionStump(1)_R1
weka.IterativeClassifierOptimizer_LogitBoost_DecisionStump(1)_Wweka.classifiers.meta.LogitBoost
weka.IterativeClassifierOptimizer_LogitBoost_DecisionStump(1)_metricRMSE
weka.IterativeClassifierOptimizer_LogitBoost_DecisionStump(1)_S1

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
0.9847
Per class
F measure
0.9337
Per class
Kappa
0.8673
KB relative information score
726.4946
Mean absolute error
0.1292
Mean prior absolute error
0.4996
Number of instances
950
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9338
Per class
Predictive accuracy
0.9337
Prior entropy
0.9995
Recall
0.9337
Per class
Relative absolute error
0.2587
Root mean prior squared error
0.4998
Root mean squared error
0.2274
Root relative squared error
0.4549
SciMark benchmark
911.0478
UserCPU time millis
50
UserCPU time millis testing
10
UserCPU time millis training
40