`housing.Rd`

Data from the Ames Assessor's Office used in assessing values of individual residential properties sold in Ames, Iowa from 2006 to 2010. This is a regression problem and the goal is to predict "SalePrice" which records the price of a home in thousands of dollars.

De Cock, D., (2011). Ames, Iowa: Alternative to the Boston housing
data as an end of semester regression project. *Journal of Statistics
Education*, 19(3), 1--14.

```
# \donttest{
## load the data
data(housing, package = "randomForestSRC")
## the original data contains lots of missing data, so impute it
## use missForest, can be slow so grow trees with small training sizes
housing2 <- impute(data = housing, mf.q = 1, sampsize = function(x){x * .1})
## same idea ... but directly use rfsrc.fast and multivariate missForest
housing3 <- impute(data = housing, mf.q = .5, fast = TRUE)
## even faster, but potentially less acurate
housing4 <- impute(SalePrice~., housing, splitrule = "random", nimpute = 1)
# }
```