eval_metrics.py 文件源码

def _r2(probabilities, targets):
  if targets.get_shape().ndims == 1:
    targets = array_ops.expand_dims(targets, -1)
  y_mean = math_ops.reduce_mean(targets, 0)
  squares_total = math_ops.reduce_sum(math_ops.square(targets - y_mean), 0)
  squares_residuals = math_ops.reduce_sum(math_ops.square(
      targets - probabilities), 0)
  score = 1 - math_ops.reduce_sum(squares_residuals / squares_total)
  return metric_ops.streaming_mean(score)