experimental/no_u_turn_sampler/logistic_regression.py
def logistic_regression(features):
  """Bayesian logistic regression, which returns labels given features."""
  coeffs = ed.MultivariateNormalDiag(
      loc=tf.zeros(features.shape[1]), name="coeffs")
  labels = ed.Bernoulli(
      logits=tf.tensordot(features, coeffs, [[1], [0]]), name="labels")
  return labels
def logistic_regression(features):
  """Bayesian logistic regression, which returns labels given features."""
  coeffs = ed.MultivariateNormalDiag(
      loc=tf.zeros(features.shape[1]), name="coeffs")
  labels = ed.Bernoulli(
      logits=tf.tensordot(features, coeffs, [[1], [0]]), name="labels")
  return labels
Bayesian logistic regression, which returns labels given features.