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4 . 1 0 LAB: Prediction with Logistic Regression The file Invistico _ Airline _ LR . csv contains information from an airline using the

4.10 LAB: Prediction with Logistic Regression
The file Invistico_Airline_LR.csv contains information from an airline using the alias Invistico Airline on customer satisfaction, as well as details on each customer. The columns of interest are Gender, Age, Class, Arrival_Delay_in_Minutes, and satisfaction.
Read the file Invistico_Airline_LR.csv into a data frame.
Obtain user defined values female, age, economy, and delay.
Re-code the categorical variables Gender, Class, and satisfaction into dummy variables.
Create a new data frame X from the predictor variables Gender_female, Age, Class_Eco, and Arrival_Delay_in_Minutes, in that order.
Create a response variable Y from the dummy variable satisfaction_satisfied.
Perform logistic regression on X and Y.
Use the user defined values to predict the probability that a customer with those values is satisfied.
Ex: If the input is 134010 the ouput is:
[0.62343979]

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