评估返回多个类的返回百分比的模型
如果有一个模型返回数据中存在的不同类别数量的矢量为百分比，那么将其评估的好方法（使用图表和/或统计数据）是什么？
例如，例如，一批池塘水含有30％细菌1和70％的细菌（数据为[0.3，0.7]。我们的模型返回35％细菌1和65％细菌2（输出为[0.35，0.65]）。我们评估了这个模型的准确性吗
？对于这种问题。
If there is a model that returns a vector of the amount of different classes present in the data as percentages, what would be a good way to evaluate it (with charts and/or statistics)?
Say, for example, that a batch of pond water contains 30% Bacteria1 and 70% Bacteria2 (data is [0.3, 0.7]. Our model returns 35% Bacteria1 and 65% Bacteria2 (output is [0.35, 0.65]). How would we evaluate the accuracy of this model?
Am I right in thinking that we can't use things like confusion matrices or ROC/AUC curves because this isn't a classification problem? I'm not sure if there exist other metrics like these ones for this kind of problem though.
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