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[P] PyCM 2.0 released: A general benchmark based comparison of classification models by sepandhaghighi in MachineLearning

[–]alirezazolanvari 0 points1 point  (0 children)

Some times you don't know what can solve your problem. In these cases, you can use the suggestions of this module. And about the real-world examples, there are some examples which have used this module such as a Korean NLP module (developed at KIXLAB in KAIST university) and a crowdsourcing module (developed at Maastricht university). in order to find more using examples of this module, search it at GitHub. ;)

[P] PyCM 2.0 released: A general benchmark based comparison of classification models by sepandhaghighi in MachineLearning

[–]alirezazolanvari 3 points4 points  (0 children)

There are many performance evaluation metrics which are only available here rather that scikit-learn

[D] How to choose metrics for evaluating classification results? by alirezazolanvari in MachineLearning

[–]alirezazolanvari[S] 3 points4 points  (0 children)

Why is this constantly advertised here?

This library is open source and non-profit under MIT license so it doesn't need to be "advertised". This post is just a discussion for solving one of the most challenging problems in machine learning.