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Implement accuracy metric for multiclass classification (#47772)

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Przemysław Witek 2019-11-21 13:07:14 +01:00 • committed by GitHub
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docs/java-rest/high-level/ml/evaluate-data-frame.asciidoc
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@ -52,7 +52,8 @@ include-tagged::{doc-tests-file}[{api}-evaluation-classification]
<2> Name of the field in the index. Its value denotes the actual (i.e. ground truth) class the example belongs to.
<3> Name of the field in the index. Its value denotes the predicted (as per some ML algorithm) class of the example.
<4> The remaining parameters are the metrics to be calculated based on the two fields described above
<5> Multiclass confusion matrix of size 3
<5> Accuracy
<6> Multiclass confusion matrix of size 3
===== Regression
@ -101,9 +102,11 @@ include-tagged::{doc-tests-file}[{api}-results-softclassification]
include-tagged::{doc-tests-file}[{api}-results-classification]
--------------------------------------------------
<1> Fetching multiclass confusion matrix metric by name
<2> Fetching the contents of the confusion matrix
<3> Fetching the number of classes that were not included in the matrix
<1> Fetching accuracy metric by name
<2> Fetching the actual accuracy value
<3> Fetching multiclass confusion matrix metric by name
<4> Fetching the contents of the confusion matrix
<5> Fetching the number of classes that were not included in the matrix
===== Regression