hw5

Problem 1

cd = read.csv("http://www.rob-mcculloch.org/data/usedcars.csv")
print(dim(cd))
## [1] 20063    11
names(cd)
##  [1] "price"        "trim"         "isOneOwner"   "mileage"      "year"        
##  [6] "color"        "displacement" "fuel"         "region"       "soundSystem" 
## [11] "wheelType"

Use a single, tree, Random Forests, and boosting to relate y=price to x=mileage.

Use the three set approach, that is, split your data into tain, val, test.

Plot your results.

Which works best ?

This is just a homework, don’t kill your self trying a ton of different tuning parameters.
Save that for the project.

Problem 2

Use a single, tree, Random Forests, and boosting to relate y=price to x1=mileage and x2=year.

Use the three set approach, that is, split your data into tain, val, test.

Plot your results.

Problem 3

Use a neural nets to relate y=price to x=mileage.

Use the three set approach, that is, split your data into tain, val, test.

Plot your results.

Keep it simple!! Single layer if you like!!

Problem 4

Use a neural nets to relate y=price to x1=mileage and x2=year.

Use the three set approach, that is, split your data into tain, val, test.

Plot your results.

Keep it simple!! Single layer if you like!!