v1.4.0 #830
MilesCranmer
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v1.4.0
#830
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What's Changed
#823 adds support for parameters in template expressions, allowing you to learn expressions under a template, that have custom coefficients which can be optimized.
Along with this, the
TemplateExpressionSpec
API has changed. (The old API will continue to function, but will not have parametric expressions available).This would learn three parameters, for the expression$y = p_1 + p_2 f(x) + p_3 f(x)^2.$
You can have multiple parameter vectors, and these parameter vectors can also be indexed by categorical features. For example:
This will learn an equation of the form:
$$y = \alpha_c,f(x_1,x_2) + \beta g(x_1 \cdot x_2)$$ $c$ is the category, $\alpha_c$ is a learned parameter specific to each category, and $\beta$ is a normal scalar category. Note that unlike ParametricExpressionSpec, this feature of TemplateExpressionSpec would have you pass the
where
category
variable inX
rather than as a category keyword (floating point versions of the categories). This difference means that in a TemplateExpressionSpec, you can actually have multiple categories!Added support for expression-level loss functions via
loss_function_expression
, which allows you to specify custom loss functions that operate on the full expression object rather than just its evaluated output. This is particularly useful when working with template expressions.Note that the old template expression syntax using function-style definitions is deprecated. Use the new, cleaner syntax instead:
Full Changelog: v1.3.1...v1.4.0
This discussion was created from the release v1.4.0.
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