DEVELOPMENT... OpenML
Run
170403

Run 170403

Task 50 (Supervised Classification) heart-h Uploaded 20-02-2015 by Felicia West
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.MultiBoostAB_MultilayerPerceptron(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.MultilayerPerceptron(2)_E20
weka.MultilayerPerceptron(2)_Ha
weka.MultilayerPerceptron(2)_L0.3
weka.MultilayerPerceptron(2)_M0.2
weka.MultilayerPerceptron(2)_N500
weka.MultilayerPerceptron(2)_S0
weka.MultilayerPerceptron(2)_V0
weka.MultiBoostAB_MultilayerPerceptron(2)_C3
weka.MultiBoostAB_MultilayerPerceptron(2)_P100
weka.MultiBoostAB_MultilayerPerceptron(2)_S1
weka.MultiBoostAB_MultilayerPerceptron(2)_I10
weka.MultiBoostAB_MultilayerPerceptron(2)_Wweka.classifiers.functions.MultilayerPerceptron

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
0.8329
Per class
F measure
0.8119
Per class
Kappa
0.5901
KB relative information score
160.489
Mean absolute error
0.0746
Mean prior absolute error
0.1867
Number of instances
294
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8114
Per class
Predictive accuracy
0.8129
Prior entropy
1.0314
Recall
0.8129
Per class
Relative absolute error
0.3997
Root mean prior squared error
0.3037
Root mean squared error
0.2676
Root relative squared error
0.8811
SciMark benchmark
940.3346
UserCPU time millis
18110
UserCPU time millis testing
30
UserCPU time millis training
18080