Calculates the mean of squared logarithmic error.

Inherits From: Metric

Formula: error = L2_norm(log(label + 1) - log(prediction + 1))**2 Note: log of an array will be elementwise, i.e. log([x1, x2]) = [log(x1), log(x2)]

The metric computes the mean of squared logarithmic error (square of L2 norm) between labels and predictions. The labels and predictions could be arrays of arbitrary dimensions. Their dimension should match.

name The name of the metric.

compute_confidence_interval Whether to compute confidence intervals for this metric.

Note that this may not completely remove the computational overhead involved in computing a given metric. This is only respected by the jackknife confidence interval method.



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Creates computations associated with metric.


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Returns serializable config.