Please help me solve this in R code. In late $2013,$ the taxi company Yourcabs.com in Bangalore, India, was facing a problem with the

drivers using their platform not showing up for their scheduled calls. Drivers would cancel their

acceptance of a call, and, if the cancellation did not occur with adequate notice, the customer

would be delayed or even left high and dry.

Yourcabs.com featured an online booking system $($though customers could phone in as well$)$ and

presented itself as a taxi booking portal. Yourcabs.com had collected data on its bookings from

$2011$ to $2013.$

The data presented for this case are a randomly selected subset of the original data, with $10,000$

rows, one row for each booking. There are $17$ input variables, including user $($customer$)$ ID$,$

vehicle model, whether the booking was made online or via a mobile app, type of travel, type of

booking package, geographic information, and the date and time of the scheduled trip. The target

variable of interest is the binary indicator of whether a ride was canceled. The overall

cancellation rate is between $7\%$ and $8\%.$

Questions

$1.$ Explore, prepare, and transform the data to facilitate predictive modeling. Describe your

process. $(5)$

$2.$ Fit the following predictive models using the same data. Vary the features and tuning

parameters. Discuss the results? $(20)$

a$)$ NB

b$)$ Decision Tree

c$)$ ANN

d$)$ SVM

$3.$ Report the predictive performance of your selected specification for each model in terms of

the confusion matrix and performance measures. How well does the model perform? $(5)$

$4.$ Based on your analysis which model would you recommend and why? $(5)$Possible Data Loss Some features might be lost if you save this workbook in the comma$-$delimited $(.$csv$)$ format. To preserve these features, save it in an Excel file format.

Yourcab$-1-$ dataset as shown in the picture