DEVELOPMENT... OpenML
Run
160278

Run 160278

Task 3943 (Supervised Classification) lymphoma_11classes Uploaded 13-02-2015 by Felicia West
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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
0.6768
Per class
F measure
0.38
Per class
Kappa
0.2706
KB relative information score
27.7688
Mean absolute error
0.1144
Mean prior absolute error
0.1551
Number of instances
96
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.3914
Per class
Predictive accuracy
0.375
Prior entropy
3.0892
Recall
0.375
Per class
Relative absolute error
0.7374
Root mean prior squared error
0.2776
Root mean squared error
0.334
Root relative squared error
1.2032
SciMark benchmark
943.2817
UserCPU time millis
58870
UserCPU time millis training
58870