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Artificial Intelligence

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    $\begingroup$ What are the parameters of a decision tree? $\endgroup$
    – ado sar
    Commented Oct 29, 2023 at 14:30
  • $\begingroup$ Criterion such as Gini, and max deep are consider as hyper parameters, DT do not have weights and biases in the same way as neural networks or other linear models and DT are considered as non parametric models. $\endgroup$
    – prosti
    Commented Oct 31, 2023 at 11:53
  • $\begingroup$ I didn't ask about hyperparameters, I asked about "parameters". The distinction between parametric and non-parametric models boils down to whether the number of parameters varies with data. So, in a decision tree what qualifies as a parameter? If we don't have a definition of what is a "parameter" in a decision tree, then statements like "the number of parameters in a decision tree vary/grow with data" are meaningless. The parameters of a decision tree could be the regions of the tree and these indeed can vary with different amount of data. $\endgroup$
    – ado sar
    Commented Oct 31, 2023 at 17:01
  • $\begingroup$ So you would like to say that DT is a parametric model. LOL. $\endgroup$
    – prosti
    Commented Oct 31, 2023 at 19:02
  • $\begingroup$ Apologize, I realized that my second comment does not make sense and I will remove it. Nevertheless, is there any definition of what a parameter, not hyperparameter is in a decision tree? $\endgroup$
    – ado sar
    Commented Oct 31, 2023 at 19:28