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Returns Python callable which indicates fitting procedure has converged.
tfp.glm.convergence_criteria_small_relative_norm_weights_change(
tolerance=1e-05, norm_order=2
)
Writing old, new model_coefficients as w0, w1, this function
defines convergence as,
relative_euclidean_norm = (tf.norm(w0 - w1, ord=2, axis=-1) /
(1. + tf.norm(w0, ord=2, axis=-1)))
reduce_all(relative_euclidean_norm < tolerance)
where tf.norm(x, ord=2) denotes the Euclidean norm of x.
Args | |
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tolerance
|
float-like Tensor indicating convergence, i.e., when
max relative Euclidean norm weights difference < tolerance.
Default value:1e-5.
</td>
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<td>norm_order</td>
<td>
Order of the norm. Default value:2` (i.e., "Euclidean norm".)
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Returns | |
|---|---|
convergence_criteria_fn
|
Python callable which returns bool Tensor
indicated fitting procedure has converged. (See inner function
specification for argument signature.)
Default value: 1e-5.
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