SossMLJ.jl

SossMLJ.jl copied to clipboard

CompatHelper not working

2

Be nice if someone can give this package some TLC. I can't get it to work in Julia 1.6 or Julia 1.8. I suspect CI would currently fail. I tried...

ablaom

Fix `predict_particles`, and implement the Brier score

15

Fixes #93 Fixes #117 Related to #52 Please note that this PR makes multiple breaking changes.

DilumAluthge

Hyperparameters should be a mutable struct (not a named tuple)

6

That way we can do hyperparameter optimization with MLJ.

DilumAluthge

Multinomial logistic regression: `predict_particles` throws `MethodError`

5

`predict_particles` throws a `MethodError` when I try to use it in the multinomial logistic regression example. The error is: `ERROR: MethodError: no method matching &(::Particles{Bool,1000}, ::Particles{Bool,1000})` Full output: ```julia julia>...

DilumAluthge

Implement a loss function for classification models

7

We currently have an example of a loss function for regression models. Specifically, we implement the root mean squared error. However, we don't currently have an example of a loss...

DilumAluthge

We need to fix the implementation of `MLJModelInterface.predict` for classifiers

5

In #91, I added an incorrect implementation of `MMI.predict` for classifiers. This allowed me to finish the pipeline, do cross validation, add additional tests, etc. But we should fix the...

DilumAluthge

Reorganization of the predictor types

6

Currently, we only have a single predictor type: ```julia struct SossMLJPredictor{M}

DilumAluthge

Shorter printing of Soss models in stack traces

5

Whenever the Soss or SossMLJ model types show up in stack traces, it is quite verbose, and makes the stack trace hard to read. Here's an example. Look e.g. at...

DilumAluthge

Alternatives for linear regression example

1

Hi @DilumAluthge , we currently have ```julia m = @model X, s, t begin p = size(X, 2) # number of features β ~ Normal(0, s) |> iid(p) # coefficients...

cscherrer

Bayesian neural networks

1

I think that Bayesian neural networks would be a natural successor to our tutorials on Bayesian GLMs. As far as the neural network library to use, I think [Flux](https://github.com/FluxML/Flux.jl) makes...

DilumAluthge