Yeah, for binary data, you can also use MulticlassClassificationEvaluator
to evaluate other metrics which BinaryClassificationEvaluator doesn't
cover, such as accuracy, f1, weightedPrecision and weightedRecall.
Thanks
Yanbo
On Thu, May 11, 2017 at 10:31 PM, Lan Jiang wrote:
> I realized that in the Spark ML, BinaryClassifcationMetrics only supports
> AreaUnderPR and AreaUnderROC. Why is that? I
>
> What if I need other metrics such as F-score, accuracy? I tried to use
> MulticlassClassificationEvaluator to evaluate other metrics such as
> Accuracy for a binary classification problem and it seems working. But I am
> not sure if there is any issue using MulticlassClassificationEvaluator
> for a binary classification. According to the Spark ML documentation "The
> Evaluator can be a RegressionEvaluator for regression problems, *a
> BinaryClassificationEvaluator for binary data, or a
> MulticlassClassificationEvaluator for multiclass problems*. "
>
> https://spark.apache.org/docs/2.1.0/ml-tuning.html
>
> Can someone shed some lights on the issue?
>
> Lan
>