Data Mining READ IN ITS ENTIRITY: I've tried this problem a couple of times and keep getting errors even with other chegg experts help.

Show how to code this using R studio? Show COMPLETE R code $-$ Start to Finish $($MAKE SURE TO TEST IT IN R yourself! $)$ I will be using Naive Bayes as the other classification model

Here the objective is to identify flights that are likely to be delayed.

You will need to do some feature engineering:

Use the variable "schedtime" to create a new variable "sched$\_$time" that indicates whether the schedule was in morning, evening

or night.

Do not use flight number as predictor

Use the flight delay data to predict the flight delay status $(0=$Ontime vs $1=$Delayed$).**$

Use logistic regression model and Na$$ve Bayes classification model

Interpret the coefficients estimated from the logistic regression model.

Provide model performance metrics for both the modes $($Logistic vs Naive Bayes $).$

Data Categories in data set that im using are as follows: "schedtime", "carrier", "deptime", "dest", "distance", "date", "flightnumber", "origin", "weather", "dayweek", "daymonth", "tailnu", and "delay"

$($Disclaimer: other experts have tried to use chatgpt and have posted answers not relevant to what needs to be done$)$