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refactor ecosystem overview (#154)
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* refactor ecosystem overview

* add fda pipeops to overview

* typo

* Update mlr-org/ecosystem.qmd

* index mlr3fda
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sebffischer committed Feb 6, 2024
1 parent 9824c81 commit cc01d4e
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2 changes: 1 addition & 1 deletion DESCRIPTION
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Expand Up @@ -56,4 +56,4 @@ Remotes:
mlr-org/mlr3proba
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
RoxygenNote: 7.3.1
2 changes: 1 addition & 1 deletion R/zzz.R
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Expand Up @@ -8,7 +8,7 @@

db = new.env()
db$index = c("base", "utils", "datasets", "data.table", "stats", "batchtools")
db$hosted = c("paradox", "mlr3misc", "mlr3", "mlr3data", "mlr3db", "mlr3proba", "mlr3pipelines", "mlr3learners", "mlr3filters", "bbotk", "mlr3tuning", "mlr3viz", "mlr3fselect", "mlr3cluster", "mlr3spatiotempcv", "mlr3spatial", "mlr3extralearners", "mlr3tuningspaces", "mlr3hyperband", "mlr3mbo", "mlr3verse", "mlr3benchmark", "mlr3oml", "mlr3batchmark", "mlr3fairness")
db$hosted = c("paradox", "mlr3misc", "mlr3", "mlr3data", "mlr3db", "mlr3proba", "mlr3pipelines", "mlr3learners", "mlr3filters", "bbotk", "mlr3tuning", "mlr3viz", "mlr3fselect", "mlr3cluster", "mlr3spatiotempcv", "mlr3spatial", "mlr3extralearners", "mlr3tuningspaces", "mlr3hyperband", "mlr3mbo", "mlr3verse", "mlr3benchmark", "mlr3oml", "mlr3batchmark", "mlr3fairness", "mlr3fda")

lgr = NULL

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103 changes: 50 additions & 53 deletions mlr-org/ecosystem.qmd
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Expand Up @@ -54,42 +54,39 @@ package_grid = function(content) {
# Text description should be one sentence
content = rowwise_table(
~category, ~name, ~status, ~url, ~text,
"core", "mlr3", "stable", "https://mlr3.mlr-org.com/", "Basic building blocks for machine learning",
"core", "mlr3verse", "stable", "https://mlr3verse.mlr-org.com/", "Meta-package intended to simplify both installation and loading of packages from the mlr3 ecosystem",
"optimization", "mlr3tuning", "stable", "https://mlr3tuning.mlr-org.com/", "Hyperparameter tuning for mlr3 learners",
"optimization", "mlr3tuningspaces", "stable", "https://mlr3tuningspaces.mlr-org.com/", "Collection of search spaces for hyperparameter tuning",
"optimization", "mlr3hyperband", "stable", "https://mlr3hyperband.mlr-org.com/", "Successive halving and hyperband tuner for mlr3tuning",
"optimization", "mlr3mbo", "stable", "https://mlr3mbo.mlr-org.com/", "Model-based optimization for mlr3tuning",
"optimization", "miesmuschel", "stable", "https://github.com/mlr-org/miesmuschel/", "Flexible mixed integer evolutionary strategies",
"optimization", "mlr3automl", "experimental", "https://github.com/mlr-org/mlr3automl/", "Automated machine learning",
"featsel", "mlr3filters", "stable", "https://mlr3filters.mlr-org.com/", "Filter Feature Selection",
"featsel", "mlr3fselect", "stable", "https://mlr3fselect.mlr-org.com/", "Wrapper Feature Selection",
"data", "mlr3db", "stable", "https://mlr3db.mlr-org.com/", "Data backend to transparently work with databases",
"data", "mlr3oml", "stable", "https://mlr3oml.mlr-org.com/", "Connector to OpenML",
"data", "mlr3data", "stable", "https://mlr3data.mlr-org.com/", "Data sets and tasks",
"learners", "mlr3learners", "stable", "https://mlr3learners.mlr-org.com/", "Essential learners for mlr3, maintained by the mlr-org team",
"learners", "mlr3extralearners", "stable", "https://mlr3extralearners.mlr-org.com/", "Extra learners for mlr3, implemented by the community",
"learners", "mlr3torch", "experimental", "https://mlr3torch.mlr-org.com", "Deep learning with Torch",
"learners", "mlr3keras", "experimental", "https://github.com/mlr-org/mlr3keras/", "Deep learning with Keras",
"visualization", "mlr3viz", "stable", "https://mlr3viz.mlr-org.com/", "Visualizations for tasks, predictions, resample results and benchmarks",
"pipelines", "mlr3pipelines", "stable", "https://mlr3pipelines.mlr-org.com/", "Dataflow programming toolkit",
"tasks", "mlr3spatiotempcv", "stable", "https://mlr3spatiotempcv.mlr-org.com/", "Spatiotemporal resampling and visualization methods",
"tasks", "mlr3cluster", "stable", "https://mlr3cluster.mlr-org.com/", "Cluster analysis",
"tasks", "mlr3proba", "stable", "https://mlr3proba.mlr-org.com/", "Probabilistic predictions",
"tasks", "mlr3ordinal", "experimental", "https://mlr3ordinal.mlr-org.com/", "Ordinal regression",
"tasks", "mlr3multioutput", "experimental", "https://github.com/mlr-org/mlr3multioutput", "Storing and working with multi-output tasks",
"tasks", "mlr3temporal", "experimental", "https://mlr3temporal.mlr-org.com/", "Time series analysis",
"tasks", "mlr3spatial", "stable", "https://mlr3spatial.mlr-org.com/", "Spatial data backends and prediction functions",
"tasks", "mlr3multilabel", "planned", "https://github.com/mlr-org/mlr3multilabel", "Multi-Label Classification",
"tasks", "mlr3fda", "experimental", "https://mlr3fda.mlr-org.com", "Functional Data Analysis",
"utils", "bbotk", "stable", "https://bbotk.mlr-org.com/", "Black-box optimization toolkit",
"utils", "paradox", "stable", "https://paradox.mlr-org.com/", "Universal parameter space description and tools",
"utils", "mlr3misc", "stable", "https://mlr3misc.mlr-org.com/", "Miscellaneous helper functions for mlr3",
"utils", "mlr3measures", "stable", "https://mlr3measures.mlr-org.com/", "Performance measures for supervised learning",
"utils", "mlr3benchmark", "stable", "https://mlr3benchmark.mlr-org.com/", "Analysis and tools for benchmarking",
"tasks", "mlr3fairness", "stable", "https://mlr3fairness.mlr-org.com/", "Fairness in Machine Learning",
"utils", "mlr3batchmark", "experimental", "https://github.com/mlr-org/mlr3batchmark/", "Connector between mlr3 and batchtools"
~category, ~name, ~status, ~url, ~text,
"core", "mlr3", "stable", "https://mlr3.mlr-org.com/", "Basic building blocks for machine learning",
"core", "mlr3verse", "stable", "https://mlr3verse.mlr-org.com/", "Meta-package intended to simplify both installation and loading of packages from the mlr3 ecosystem",
"core", "mlr3pipelines", "stable", "https://mlr3pipelines.mlr-org.com/", "Dataflow programming toolkit",
"optimization", "mlr3tuning", "stable", "https://mlr3tuning.mlr-org.com/", "Hyperparameter tuning for mlr3 learners",
"optimization", "mlr3tuningspaces", "stable", "https://mlr3tuningspaces.mlr-org.com/", "Collection of search spaces for hyperparameter tuning",
"optimization", "mlr3hyperband", "stable", "https://mlr3hyperband.mlr-org.com/", "Successive halving and hyperband tuner for mlr3tuning",
"optimization", "mlr3mbo", "stable", "https://mlr3mbo.mlr-org.com/", "Model-based optimization for mlr3tuning",
"optimization", "miesmuschel", "stable", "https://github.com/mlr-org/miesmuschel/", "Flexible mixed integer evolutionary strategies",
"optimization", "mlr3automl", "experimental", "https://github.com/mlr-org/mlr3automl/", "Automated machine learning",
"optimization", "bbotk", "stable", "https://bbotk.mlr-org.com/", "Black-box optimization toolkit",
"featsel", "mlr3filters", "stable", "https://mlr3filters.mlr-org.com/", "Filter Feature Selection",
"featsel", "mlr3fselect", "stable", "https://mlr3fselect.mlr-org.com/", "Wrapper Feature Selection",
"data", "mlr3db", "stable", "https://mlr3db.mlr-org.com/", "Data backend to transparently work with databases",
"data", "mlr3oml", "stable", "https://mlr3oml.mlr-org.com/", "Connector to OpenML",
"data", "mlr3data", "stable", "https://mlr3data.mlr-org.com/", "Data sets and tasks",
"learners", "mlr3learners", "stable", "https://mlr3learners.mlr-org.com/", "Essential learners for mlr3, maintained by the mlr-org team",
"learners", "mlr3extralearners", "stable", "https://mlr3extralearners.mlr-org.com/", "Extra learners for mlr3, implemented by the community",
"learners", "mlr3torch", "experimental", "https://mlr3torch.mlr-org.com", "Deep learning with Torch",
"analysis", "mlr3viz", "stable", "https://mlr3viz.mlr-org.com/", "Visualizations for tasks, predictions, resample results and benchmarks",
"analysis", "mlr3benchmark", "stable", "https://mlr3benchmark.mlr-org.com/", "Analysis and tools for benchmarking",
"tasks", "mlr3spatiotempcv", "stable", "https://mlr3spatiotempcv.mlr-org.com/", "Spatiotemporal resampling and visualization methods",
"tasks", "mlr3cluster", "stable", "https://mlr3cluster.mlr-org.com/", "Cluster analysis",
"tasks", "mlr3proba", "stable", "https://mlr3proba.mlr-org.com/", "Probabilistic predictions",
"tasks", "mlr3temporal", "experimental", "https://mlr3temporal.mlr-org.com/", "Time series analysis",
"tasks", "mlr3spatial", "stable", "https://mlr3spatial.mlr-org.com/", "Spatial data backends and prediction functions",
"tasks", "mlr3fda", "experimental", "https://mlr3fda.mlr-org.com", "Functional Data Analysis",
"tasks", "mlr3fairness", "stable", "https://mlr3fairness.mlr-org.com/", "Fairness in Machine Learning",
"utils", "paradox", "stable", "https://paradox.mlr-org.com/", "Universal parameter space description and tools",
"utils", "mlr3misc", "stable", "https://mlr3misc.mlr-org.com/", "Miscellaneous helper functions for mlr3",
"utils", "mlr3measures", "stable", "https://mlr3measures.mlr-org.com/", "Performance measures for supervised learning",
"parallelization", "mlr3batchmark", "experimental", "https://github.com/mlr-org/mlr3batchmark/", "Connector between mlr3 and batchtools",
"parallelization", "rush", "experimental", "https://github.com/mlr-org/rush", "Asynchronous parallelization"
)
# add CRAN link
content[, on_cran := name %in% rownames(available.packages(repos = "https://cloud.r-project.org"))]
Expand All @@ -109,59 +106,59 @@ setkeyv(content, c("category", "status"))
package_grid(content[.("core")])
```


## <i class="bi-sliders"></i> Optimization
## <i class="bi-pen"></i> Learners

```{r}
#| echo: false
package_grid(content[.("optimization")])
package_grid(content[.("learners")])
```

## <i class="bi-funnel"></i> Feature Selection
## <i class="bi-sliders"></i> Optimization

```{r}
#| echo: false
package_grid(content[.("featsel")])
package_grid(content[.("optimization")])
```

## <i class="bi-hdd"></i> Data
## <i class="bi-list-task"></i> Tasks and Datatypes

```{r}
#| echo: false
package_grid(content[.("data")])
package_grid(content[.("tasks")])
```

## <i class="bi-pen"></i> Learners
## <i class="bi-funnel"></i> Feature Selection

```{r}
#| echo: false
package_grid(content[.("learners")])
package_grid(content[.("featsel")])
```

## <i class="bi-bar-chart-line"></i> Visualization
## <i class="bi-hdd"></i> Data

```{r}
#| echo: false
package_grid(content[.("visualization")])
package_grid(content[.("data")])
```

## <i class="bi-share"></i> Pipelines

## <i class="bi-bar-chart-line"></i> Analysis

```{r}
#| echo: false
package_grid(content[.("pipelines")])
package_grid(content[.("analysis")])
```

## <i class="bi-list-task"></i> Tasks
## <i class="bi-balloon"></i> Utilities

```{r}
#| echo: false
package_grid(content[.("tasks")])
package_grid(content[.("utils")])
```

## <i class="bi-balloon"></i> Utilities
## <i class="bi-share"></i> Parallelization

```{r}
#| echo: false
package_grid(content[.("utils")])
package_grid(content[.("parallelization")])
```
1 change: 1 addition & 0 deletions mlr-org/pipeops.qmd
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Expand Up @@ -12,6 +12,7 @@ toc: false
library("mlr3verse")
library("mlr3proba")
library("mlr3fda")
```

Objects of class `r ref("PipeOp")` are the building blocks to compose linear machine learning pipelines and non-linear `r ref("Graph", text = "Graphs")`.
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