Values greater than the threshold map to 1, while values less than or equal to the threshold map to 0. With the default threshold of 0, only positive values map to 1.

Options

• :threshold (float/0) - Feature values below or equal to this are replaced by 0, above it by 1. Threshold may not be less than 0 for operations on sparse matrices. The default value is 0.0.

Examples

iex> t = Nx.tensor([[0, 0, 0], [3, 4, 5], [-2, 4, 3]])
iex> Scholar.Preprocessing.Binarizer.fit_transform(t, threshold: 3.0)
#Nx.Tensor<
  u8[3][3]
  [
    [0, 0, 0],
    [0, 1, 1],
    [0, 1, 0]
  ]
>
iex> t = Nx.tensor([[0, 0, 0], [3, 4, 5], [-2, 4, 3]])
iex> Scholar.Preprocessing.Binarizer.fit_transform(t,threshold: 0.4)
#Nx.Tensor<
  u8[3][3]
  [
    [0, 0, 0],
    [1, 1, 1],
    [0, 1, 1]
  ]
>copy