I am trying to create Bayesian network in R and inference. I am not sure if my bayesian network is correct or wrong. But somehow it does not look good. I am sharing my code here. please create a inference now. # Load necessary libraries

library$($readr$)$

library$($bnlearn$)$

library$($gRain$)$

library$($ggplot$2)$

library$($reshape$2)$

library$($forcats$)$

library$($dplyr$)$

# Load data

data $<-$ read.csv$("$F:$/2$nd Semester$/$Data Processing$/$Bayesian$/$Dataset$/$archive $(2)/$cleaned$.$csv$")$

# Convert all columns to factors

data $<-$ lapply$($data$,$ as$.$factor$)$

data $<-$ data.frame$($data$)$

# levels for specific columns

levels$\_$vehiclemovement $=$ c$("$Enteringajunction$",$ "Getting off", "Going straight",

"Moving Backward","Other","Overtaking","Parked","Reversing",

"Stopping","Turnover","U$-$Turn","Unknown","Waiting to go$")$

levels$($data$Vehicle$\_$movement$)=$ levels$\_$vehiclemovement

levels$\_$causeofaccident $=$ c$("$ChangeLane$",$ "ChangeLane", "DriveHighOrCareless",

"DriveHighOrCareless", "DriveLeft", "DriveAlcohol",

"DriveAlcohol", "Other", "Other","MovingBackward",

"NoDistance", "NoPriority","NoPriority", "Other","Other",

"Other","Other","Other","Other","Other"$)$

levels$($data$Cause$\_$of$\_$accident$)=$levels$\_$causeofaccident

levels$\_$Education $=$ c$("$AboveHighSchool$",$"ElementarySchool","HighSchool","Other",

"JuniorHighSchool","Unknown", "Other"$)$

levels$($data$Education$)=$ levels$\_$Education

levels$\_$drivingexperience $=$c$("1-2$yr$","2-5$yr$","5-10$yr$",$"Above $10$yr$",$"Below$1$yr$",$"NoLicence",

"Unknown","Unknown"$)$

levels$($data$Driving$\_$experience$)=$levels$\_$drivingexperience

levels$\_$lanes$=$ c$("$DoubleCarriageway$($median$)",$"OneWay","other","Twoway$($divided with broken lines road marking$)",$

"TwoWay$($divided with solid lines road marking$)",$"UndividedTwoWay","Unknown"$)$

levels$($data$Lanes$\_$or$\_$Medians$)=$levels$\_$lanes

levels$\_$lightconditions $=$ c$("$Darknesslightslit$",$"Darknesslightsunlit",

"lightsUnlitDarkness","NoLighting","NoLighting"$)$

levels$($data$Light$\_$conditions$)=$levels$\_$lightconditions

levels$\_$roadSurface $=$ c$("$AsphaltRoads$",$"AsphaltsRoadswithSomeDistress","EarthRoads",

"GravelRoads","Other","Unknown"$)$

levels$($data$Road$\_$surface$\_$type$)=$levels$\_$roadSurface

levels$\_$weatherconditions $=$ c$("$Cloudy$",$"FogOrMist","Normal","Other","Raining",

"RainingAndWindy","Snow","Unknown","Windy"$)$

levels$($data$Weather$\_$conditions$)=$levels$\_$weatherconditions

levels$\_$collision $=$ c$("$CollisionWithAnimals$",$"CollisionWithPedestrians",

"CollisionWithRoadSideParkedVehicle",

"CollisionWithRoadsideObjects","FallFromVehicles","Other","RollOver","Unknown","VehicleWithVehicleCollision","WithTrain"$)$

levels$($data$Type$\_$of$\_$collision$)=$levels$\_$collision

str$($data$)$

summary$($data$)$

bn$\_$structure $<-$ hc$($data$)$

plot$($bn$\_$structure$)$

mmhc

h$2$pc$($data$)$

network $=$ hc$($data$)$

graphviz.plot$($network$,$shape $=$ "rectangle"$)$