[source] # Xavier 2 The Xavier 2 initializer draws from a uniform distribution [-limit, limit] where *limit* is equal 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](../activation-functions/hyperbolic-tangent.md) and [Softsign](../activation-functions/softsign.md). ## Parameters This initializer does not have any parameters. ## Example ```php use Rubix\ML\NeuralNet\Initializers\Xavier2; $initializer = new Xavier2(); ``` ## References [^1]: X. Glorot et al. (2010). Understanding the Difficulty of Training Deep Feedforward Neural Networks.