Create a decision tree using gini index as the criterion

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Reference no: EM133914218

Problem

Drop the column "customer_id" from the dataset. Remove all of the observations with any missing values. Building the Decision Tree in Python 8. Use "sklearn.tree" packages to create decisions trees as follows and answer the questions (random_state = 42). Create a decision tree using gini index as the criterion. Get the instant assignment help. Use the variable churn as the target (class) variable and the variables country, gender, age, tenure, and estimated_salary as the predictors (use default setting). Make sure to convert categorical columns into dummy variables and partition the dataset into training and test sets. Paste the tree in the Word document.

Reference no: EM133914218

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