Skip to content

Normal

Random normal initializer which simulate a normal distribution with specified parameters.

Parameters

  • mu

    Type → float

    Default → 0.0

    The mean of the normal distribution

  • sigma

    Type → float

    Default → 1.0

    The standard deviation of the normal distribution

  • seed

    Type → int | None

    Default → None

    Random number generation seed that can be set for reproducibility.

Examples

from river import optim

init = optim.initializers.Normal(mu=0, sigma=1, seed=42)

init(shape=1)
np.float64(0.4967141...)

init(shape=2)
array([-0.1382643 ,  0.64768854])

Methods

call

Returns a fresh set of weights.

The return type is shape-dependent (a scalar when shape == 1, otherwise an array), and these values are routinely used as collections.defaultdict factories elsewhere, so the return is intentionally left dynamic.

Parameters

  • shape — int — defaults to 1