From 794be245edd27485dd570246b27254d8166dc5e2 Mon Sep 17 00:00:00 2001 From: "Anthony D. Blaom" Date: Mon, 23 Dec 2024 15:07:00 +1300 Subject: [PATCH] update road map --- ROADMAP.md | 51 +++++++-------------------------------------------- 1 file changed, 7 insertions(+), 44 deletions(-) diff --git a/ROADMAP.md b/ROADMAP.md index c3ba73fa3..78268ce20 100644 --- a/ROADMAP.md +++ b/ROADMAP.md @@ -1,6 +1,9 @@ # Road map -February 2020; updated, July 2023 +February 2020; updated, December 2024 + +The road map below is more big-picture; to get into the weeds, see also [this GH +Project](https://github.com/orgs/JuliaAI/projects/1). Please visit [contributing guidelines](CONTRIBUTING.md) if interested in contributing to MLJ. @@ -29,20 +32,14 @@ in contributing to MLJ. ### Priorities -Priorities are somewhat fluid, depending on funding offers and -available talent. Rough priorities for the core development team at -present are marked with **†** below. However, we are always keen to -review external contributions in any area. +Priorities are somewhat fluid, depending on funding offers and available talent. However, +we are always keen to review external contributions in any area. ## Future enhancements -The following road map is more big-picture; see also [this -GH Project](https://github.com/orgs/JuliaAI/projects/1). - - ### Adding models -- [ ] **Integrate deep learning** using [Flux.jl](https://github.com/FluxML/Flux.jl.git) deep learning. [Done](https://github.com/FluxML/MLJFlux.jl) but can +- [x] **Integrate deep learning** using [Flux.jl](https://github.com/FluxML/Flux.jl.git) deep learning. [Done](https://github.com/FluxML/MLJFlux.jl) but can improve the experience by: - [x] finishing iterative model wrapper [#139](https://github.com/JuliaAI/MLJ.jl/issues/139) @@ -71,20 +68,11 @@ GH Project](https://github.com/orgs/JuliaAI/projects/1). ### Enhancing core functionality -- [x] Iterative model control [#139](https://github.com/JuliaAI/MLJ.jl/issues/139). [Done](https://github.com/JuliaAI/MLJIteration.jl) - - [ ] **†** Add more tuning strategies. See [here](https://github.com/JuliaAI/MLJTuning.jl#what-is-provided-here) for complete wish-list. Particular focus on: - - [x] random search - ([#37](https://github.com/JuliaAI/MLJ.jl/issues/37)) - (done) - - - [x] Latin hypercube - [done](https://github.com/JuliaAI/MLJTuning.jl/pull/96) - - [ ] Bayesian methods, starting with Gaussian Process methods a la PyMC3. Some preliminary research done. @@ -99,8 +87,6 @@ GH Project](https://github.com/orgs/JuliaAI/projects/1). - [ ] Genetic algorithms [#38](https://github.com/JuliaAI/MLJ.jl/issues/38) - - [ ] Particle Swarm Optimization (current WIP, GSoC project @lhnguyen-vn) - - [ ] tuning strategies for non-Cartesian spaces of models [MLJTuning #18](https://github.com/JuliaAI/MLJTuning.jl/issues/18), architecture search, and other AutoML workflows @@ -111,16 +97,6 @@ GH Project](https://github.com/orgs/JuliaAI/projects/1). (boosting, etc) and migrate to a separate repository? [#363](https://github.com/JuliaAI/MLJ.jl/issues/363) -- [ ] **†** Enhance complex model composition: - - - [x] Introduce a canned - stacking model wrapper ([POC](https://JuliaAI.github.io/DataScienceTutorials.jl/getting-started/stacking/)). WIP @olivierlabayle - - - [ ] Get rid of macros for creating pipelines and possibly - implement target transforms as wrappers ([MLJBase - #594](https://github.com/JuliaAI/MLJ.jl/issues/594)) - WIP @CameronBieganek and @ablaom - ### Broadening scope @@ -137,12 +113,6 @@ GH Project](https://github.com/orgs/JuliaAI/projects/1). [this proposal](https://julialang.org/jsoc/gsoc/MLJ/#interpretable_machine_learning_in_julia) -- [x] Spin-off a stand-alone measures (loss functions) package - (currently - [here](https://github.com/JuliaAI/MLJBase.jl/tree/master/src/measures)). Introduce - measures for multi-targets [MLJBase - #502](https://github.com/JuliaAI/MLJBase.jl/issues/502). - - [ ] Add sparse data support and better support for NLP models; we could use [NaiveBayes.jl](https://github.com/dfdx/NaiveBayes.jl) as a POC (currently wrapped only for dense input) but the API @@ -171,8 +141,6 @@ GH Project](https://github.com/orgs/JuliaAI/projects/1). - [ ] provide visualizations that MLR3 provides via [mlr3viz](https://github.com/mlr-org/mlr3viz) -- [ ] Extend API to accommodate outlier detection, as provided by [OutlierDetection.jl](https://github.com/davnn/OutlierDetection.jl) [#780](https://github.com/JuliaAI/MLJ.jl/issues/780) WIP @davn and @ablaom - - [ ] Add more pre-processing tools: - [x] missing value imputation using Gaussian Mixture Model. Done, @@ -182,8 +150,6 @@ GH Project](https://github.com/orgs/JuliaAI/projects/1). training on a large collection of datasets with manually labelled scitype schema. -- [ ] Add integration with [MLFlow](https://julialang.org/jsoc/gsoc/MLJ/#mlj_and_mlflow_integration); see [this proposal](https://julialang.org/jsoc/gsoc/MLJ/#mlj_and_mlflow_integration) - - [ ] Extend integration with [OpenML](https://www.openml.org) WIP @darenasc @@ -203,6 +169,3 @@ GH Project](https://github.com/orgs/JuliaAI/projects/1). - [ ] Automated estimates of cpu/memory requirements [#71](https://github.com/JuliaAI/MLJ.jl/issues/71) -- [x] Add multithreading to tuning [MLJTuning - #15](https://github.com/JuliaAI/MLJTuning.jl/issues/15) - [Done](https://github.com/JuliaAI/MLJTuning.jl/pull/42).