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I can reproduce this problem for an even more easily separable dataset: The ideal tree for it should be as follows: However, when I run DecisionTreeClassifier with the maximal depth = 2 in scikit-learn many times, it splits the dataset randomly and never gets it right. This is an example of 4 different runs: The problem is that scikit-learn has only two ...


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Yes, ML can fit a curve based on examples that include hyperparameters but not a model specification. To do this, you need to specify a family of models that is large enough to include the true model. You can then treat this as learning a relationship from 4 inputs to a single output. For example, suppose you are willing to make only the following ...


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