When to use what

Based on the lecture on decision tree, we can conclude that its used for categorical dependent variables.

  1. Can it be used for continuous dependent variables

  2. How can we know when to use decisions tree or logistics regression?

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Hey, Decision Trees’ beauty is it can be used for both regression and classification.
Generally speaking, there is no way to know when to use what model, it’s all about trying and figuring out. Both Logistic Regression and Decision Tree are used for Classification, but which performs better is what you have to try and figure out.
PS: I have seen Random forest(Will be taught in the next lecture) working better than both Decision Tree and Logistic Regression, but again that might not be true for every case.

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Thank you all i appreciate

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There is some information
** Decision trees.*

** Logistics regression*

1.It is one way to display an algorithm that only contains conditional control statements. Decision trees are commonly used in operations research, specifically in decision analysis, to help identify a strategy most likely to reach a goal, but are also a popular tool in machine learning.

2.Logistic Regression is used when the dependent variable(target) is categorical. For example, To predict whether an email is spam (1) or (0) Whether the tumor is malignant (1) or not (0)