Dataset taken from the StatLib library which is maintained at Carnegie Mellon University.
dataset_boston_housing(
path = "boston_housing.npz",
test_split = 0.2,
seed = 113L,
convert = TRUE
)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>Path where to cache the dataset locally (relative to ~/.keras/datasets).
fraction of the data to reserve as test set.
Random seed for shuffling the data before computing the test split.
When TRUE (default) the datasets are returned as R arrays.
If FALSE, objects are returned as NumPy arrays.
Other datasets:
dataset_california_housing()
dataset_cifar10()
dataset_cifar100()
dataset_fashion_mnist()
dataset_imdb()
dataset_mnist()
dataset_reuters()