Darren Colby
Darren Colby
Currently, classification is done by just using the sigmoid activation function, which is basically just regression. This could potentially lead to predicted probabilities being outside of [0, 1]. Instead, for...
Add W parameter for covariates for the treatment function in double machine learning, X learning, doubly robust estimation, and R learning.
This is essentially the same thing as https://github.com/dscolby/CausalELM.jl/issues/36. We will use the clipping function because it preserves class predictions and constrains the predictions within the range of natural values.
Priority should probably be integration with CUDA, then Intel, then ATI, then Mac. In theory this should be easy but we should watch for type instability.
Explain that the final model is linear and that the functional form is partially linear and semiparametric.
Specifically incorporate accuracy because MSE doesn't work for classification.
Generate interpretations from model validation and return them as strings.
While all of the examples in the documentation are from the unit tests and have all passed, it would be better to make as many doc tests as possible. However,...
This is not a priority and it will take a while. It is going to require working with CSS. Right now the theme is clean but the color palette is...