Login Register

tf.contrib.distributions.Gamma.entropy()

tf.contrib.distributions.Gamma.entropy(name='entropy')

Shanon entropy in nats.

Additional documentation from Gamma:

This is defined to be

entropy = alpha - log(beta) + log(Gamma(alpha))
+ (1-alpha)digamma(alpha)

where digamma(alpha) is the digamma function.

Links:

https://www.tensorflow.org/versions/master/api_docs/python/contrib.distributions.html#Gamma.entropy

doc_TensorFlow

2025-01-10 15:47:30

Comments

Leave a Comment

Please login to continue.

Popular Articles

tf.contrib.distributions.Gamma class tf.contrib.distributions.Gamma The Gamma distribution with parameter alpha and beta. The parameters are the shape and inverse scale parameters

tf.contrib.distributions.Gamma.dtype tf.contrib.distributions.Gamma.dtype The DType of Tensors handled by this Distribution.

tf.contrib.distributions.Gamma.sample() tf.contrib.distributions.Gamma.sample(sample_shape=(), seed=None, name='sample') Generate samples of the specified shape. Note that a call to sample

tf.contrib.distributions.Gamma.pdf() tf.contrib.distributions.Gamma.pdf(value, name='pdf') Probability density function. Args: value: float or double Tensor. name: The name to give th

tf.contrib.distributions.Gamma.mean() tf.contrib.distributions.Gamma.mean(name='mean') Mean.