Comparison between logistic regression and decision trees

Before we dive into the coding details of decision trees, here, we will quickly compare the differences between logistic regression and decision trees, so that we will know which model is better and in what way.

Logistic regression	Decision trees
Logistic regression model looks like an equation between independent variables with respect to its dependent variable.	Tree classifiers produce rules in simple English sentences, which can be easily explained to senior management.
Logistic regression is a parametric model, in which the model is defined by having parameters multiplied by independent variables to predict the dependent variable.	Decision Trees are a non-parametric model, in which no pre-assumed parameter exists. Implicitly performs variable screening or feature selection.
Assumptions are made on response (or dependent) variable, with binomial or Bernoulli distribution.	No assumptions are made on the underlying distribution of the data...