OneVsRestClassifier already implements Binary Relevance. What is unclear
about our documentation on model evaluation and metrics?
On 25 March 2016 at 00:13, Enise Basaran <basaranen...@gmail.com> wrote:
> Hi everyone,
>
> I want to learn binary classifier evaluation metrics please. I implemented
> "Binary Relevance" method for multilabel classification.*[1] * My
> classifiers say "Yes" or "No". How can I calculate accuracy score of my
> dataset, what metrics can I use for my binary classifiers? Thanks in
> advance.
>
>
> *[1] Binary Relevance (BR)* is one of the most popular approaches as a
> trans-formation method that actually creates k datasets (k = |L|, total
> number of classes), each for one
> class label and trains a classifier on each of these datasets. Each of
> these datasets contains the same number of instances as the original data,
> but each dataset D λ j , 1 ≤ j ≤ k positively labels instances that belong
> to class λ j and negative otherwise.
>
> Sincerely,
>
>
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