KINDLY ANSWER USING PYTHON ONLY

$9\mathrm{.}2$ Predicting Delayed Flights. The file FlightDelays.csv contains information on all commercial flights departing the Washington, DC area and arriving at New York during January $2004.$ For each flight, there is information on the departure and arrival airports, the distance of the route, the scheduled time and date of the flight, and so on$.$ The variable that we are trying to predict is whether or not a flight is delayed. A delay is defined as an arrival that is at least $15$ minutes later than scheduled.

Data Preprocessing. Transform variable day of week $($DAY$\_$WEEK$)$ info a cate$-$ gorical variable. Bin the scheduled departure time into eight bins. Use these and all

other columns as predictors $($excluding DAY$\_$OF$\_$MONTH$).$ Partition the data into training $(60\%)$ and validation $(40\%)$ sets.

a$.$ Fit a classification tree to the flight delay variable using all the relevant predictors. Do not include DEP$\_$TIME $($actual departure time$)$ in the model because it is unknown at the time of prediction $($unless we are generating our predictions of delays after the plane takes off, which is unlikely$).$ Use a tree with maximum depth $8$ and minimum impurity decrease $=0\mathrm{.}01.$ Express the resulting tree as a set of rules.

b$.$ If you needed to fly between DCA and EWR on a Monday at $7$:$00$ AM$,$ would you be able to use this tree? What other information would you need? Is it available in practice? What information is redundant?

c$.$ Fit the same tree as in $($a$),$ this time excluding the Weather predictor. Display both the resulting $($small$)$ tree and the full$-$grown tree. You will find that the small tree contains a single terminal node.

i$.$ Howisthesmalltreeusedforclassification?$($Whatistheruleforclassifying$?)$

ii$.$ Towhatisthisruleequivalent?

iii. Examine the full$-$grown tree. What are the top three predictors according to this tree?

iv$.$ Why,technically,doesthesmalltreeresultinasinglenode?

v$.$ Whatisthedisadvantageofusingthetoplevelsofthefull$-$growntreeasopposed

to the small tree?

vi$.$ Compare this general result to that from logistic regression in the example in Chapter $10.$ What are possible reasons for the classification tree$$s failure to find a good predictive model?