DEVELOPMENT... OpenML
Run
158170

Run 158170

Task 3807 (Supervised Classification) echoMonths 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
0.7945
Per class
F measure
0.7223
Per class
Kappa
0.4452
KB relative information score
51.2891
Mean absolute error
0.3098
Mean prior absolute error
0.4999
Number of instances
130
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7246
Per class
Predictive accuracy
0.7231
Prior entropy
0.9998
Recall
0.7231
Per class
Relative absolute error
0.6197
Root mean prior squared error
0.4999
Root mean squared error
0.4384
Root relative squared error
0.8769
SciMark benchmark
932.3943
UserCPU time millis
10
UserCPU time millis training
10