Boston housing price regression dataset

Dataset taken from the StatLib library which is maintained at Carnegie Mellon University.

Usage

dataset_boston_housing(
  path = "boston_housing.npz",
  test_split = 0.2,
  seed = 113L,
  convert = TRUE
)

Arguments

path

Path where to cache the dataset locally (relative to ~/.keras/datasets).

test_split

fraction of the data to reserve as test set.

seed

Random seed for shuffling the data before computing the test split.

convert

When TRUE (default) the datasets are returned as R arrays. If FALSE, objects are returned as NumPy arrays.

Value

Lists of training and test data: train$x, train$y, test$x, test$y.

Samples contain 13 attributes of houses at different locations around the Boston suburbs in the late 1970s. Targets are the median values of the houses at a location (in k$).

str(dataset_boston_housing())

## List of 2
##  $ train:List of 2
##   ..$ x: num [1:404, 1:13] 1.2325 0.0218 4.8982 0.0396 3.6931 ...
##   ..$ y: num [1:404(1d)] 15.2 42.3 50 21.1 17.7 18.5 11.3 15.6 15.6 14.4 ...
##  $ test :List of 2
##   ..$ x: num [1:102, 1:13] 18.0846 0.1233 0.055 1.2735 0.0715 ...
##   ..$ y: num [1:102(1d)] 7.2 18.8 19 27 22.2 24.5 31.2 22.9 20.5 23.2 ...

str(dataset_boston_housing(convert = FALSE))

## List of 2
##  $ train:List of 2
##   ..$ x: <numpy.ndarray shape(404,13), dtype=float64>
##   ..$ y: <numpy.ndarray shape(404), dtype=float64>
##  $ test :List of 2
##   ..$ x: <numpy.ndarray shape(102,13), dtype=float64>
##   ..$ y: <numpy.ndarray shape(102), dtype=float64>

See also

Other datasets:
dataset_california_housing()
dataset_cifar10()
dataset_cifar100()
dataset_fashion_mnist()
dataset_imdb()
dataset_mnist()
dataset_reuters()