how can i compare two classification algorithms?
Performance of a model can be judged along several dimensions:

Accuracy - Is the train-test validation performing well?

Overfitting - Is the difference between training score and the validation score minimal?

Efficiency - Is the model light-weight, does it compute and calculate fast?

Complexity - Is the model easy to explain, does it use minimal transformations?

Deployability - Will I be able to deploy and use the model easily?


Rather than from a pure statistics perspective (which is just dimension 1 &amp; 2) judge the models from all perspecties. If they still perform equally well than they are in fact equal (not surprising for two similiar models performed on the same data set).