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Xavier 2#

The Xavier 2 initializer draws from a uniform distribution [-limit, limit] where limit is squal to (6 / (fanIn + fanOut)) ** 0.25. This initializer is best suited for layers that feed into an activation layer that outputs values between -1 and 1 such as Hyperbolic Tangent and Softsign.

Parameters#

This initializer does not have any parameters.

Example#

use Rubix\ML\NeuralNet\Initializers\Xavier2;

$initializer = new Xavier2();

References#

  • X. Glorot et al. (2010). Understanding the Difficulty of Training Deep Feedforward Neural Networks.