mlr3 - Machine Learning in R - Next Generation

Efficient, object-oriented programming on the building blocks of machine learning. Provides 'R6' objects for tasks, learners, resamplings, and measures. The package is geared towards scalability and larger datasets by supporting parallelization and out-of-memory data-backends like databases. While 'mlr3' focuses on the core computational operations, add-on packages provide additional functionality.

Last updated 2 months ago

classificationdata-sciencemachine-learningmlr3regression

14.77 score 953 stars 32 dependents 1.9k scripts 10k downloads

mlr3pipelines - Preprocessing Operators and Pipelines for 'mlr3'

Dataflow programming toolkit that enriches 'mlr3' with a diverse set of pipelining operators ('PipeOps') that can be composed into graphs. Operations exist for data preprocessing, model fitting, and ensemble learning. Graphs can themselves be treated as 'mlr3' 'Learners' and can therefore be resampled, benchmarked, and tuned.

Last updated 2 months ago

baggingdata-sciencedataflow-programmingensemble-learningmachine-learningmlr3pipelinespreprocessingstacking

12.11 score 141 stars 7 dependents 428 scripts 4.6k downloads

mlr3tuning - Hyperparameter Optimization for 'mlr3'

Hyperparameter optimization package of the 'mlr3' ecosystem. It features highly configurable search spaces via the 'paradox' package and finds optimal hyperparameter configurations for any 'mlr3' learner. 'mlr3tuning' works with several optimization algorithms e.g. Random Search, Iterated Racing, Bayesian Optimization (in 'mlr3mbo') and Hyperband (in 'mlr3hyperband'). Moreover, it can automatically optimize learners and estimate the performance of optimized models with nested resampling.

Last updated 1 months ago

bbotkhyperparameter-optimizationhyperparameter-tuningmachine-learningmlr3optimizationtunetuning

11.55 score 55 stars 10 dependents 380 scripts 5.3k downloads

paradox - Define and Work with Parameter Spaces for Complex Algorithms

Define parameter spaces, constraints and dependencies for arbitrary algorithms, to program on such spaces. Also includes statistical designs and random samplers. Objects are implemented as 'R6' classes.

Last updated 6 months ago

experimental-designhyperparametersmlr3transformations

11.47 score 29 stars 35 dependents 314 scripts 5.5k downloads

mlr3learners - Recommended Learners for 'mlr3'

Recommended Learners for 'mlr3'. Extends 'mlr3' with interfaces to essential machine learning packages on CRAN. This includes, but is not limited to: (penalized) linear and logistic regression, linear and quadratic discriminant analysis, k-nearest neighbors, naive Bayes, support vector machines, and gradient boosting.

Last updated 2 months ago

classificationlearnersmachine-learningmlr3regression

11.41 score 91 stars 9 dependents 1.5k scripts 4.2k downloads

mlr3misc - Helper Functions for 'mlr3'

Frequently used helper functions and assertions used in 'mlr3' and its companion packages. Comes with helper functions for functional programming, for printing, to work with 'data.table', as well as some generally useful 'R6' classes. This package also supersedes the package 'BBmisc'.

Last updated 2 months ago

machine-learningmiscellaneousmlr3

10.36 score 12 stars 39 dependents 302 scripts 7.7k downloads

bbotk - Black-Box Optimization Toolkit

Features highly configurable search spaces via the 'paradox' package and optimizes every user-defined objective function. The package includes several optimization algorithms e.g. Random Search, Iterated Racing, Bayesian Optimization (in 'mlr3mbo') and Hyperband (in 'mlr3hyperband'). bbotk is the base package of 'mlr3tuning', 'mlr3fselect' and 'miesmuschel'.

Last updated 1 months ago

bbotkblack-box-optimizationdata-sciencehyperparameter-optimizationhyperparameter-tuningmachine-learningmlr3optimization

9.93 score 22 stars 13 dependents 165 scripts 5.4k downloads

mlr3viz - Visualizations for 'mlr3'

Visualization package of the 'mlr3' ecosystem. It features plots for mlr3 objects such as tasks, learners, predictions, benchmark results, tuning instances and filters via the 'autoplot()' generic of 'ggplot2'. The package draws plots with the 'viridis' color palette and applies the minimal theme. Visualizations include barplots, boxplots, histograms, ROC curves, and Precision-Recall curves.

Last updated 2 months ago

ggplot2mlr3visualizationvisualizations

9.61 score 43 stars 5 dependents 378 scripts 3.2k downloads

mlr3extralearners - Extra Learners For mlr3

Extra learners for use in mlr3.

Last updated 2 months ago

9.23 score 94 stars 474 scripts

mlr3mbo - Flexible Bayesian Optimization

A modern and flexible approach to Bayesian Optimization / Model Based Optimization building on the 'bbotk' package. 'mlr3mbo' is a toolbox providing both ready-to-use optimization algorithms as well as their fundamental building blocks allowing for straightforward implementation of custom algorithms. Single- and multi-objective optimization is supported as well as mixed continuous, categorical and conditional search spaces. Moreover, using 'mlr3mbo' for hyperparameter optimization of machine learning models within the 'mlr3' ecosystem is straightforward via 'mlr3tuning'. Examples of ready-to-use optimization algorithms include Efficient Global Optimization by Jones et al. (1998) <doi:10.1023/A:1008306431147>, ParEGO by Knowles (2006) <doi:10.1109/TEVC.2005.851274> and SMS-EGO by Ponweiser et al. (2008) <doi:10.1007/978-3-540-87700-4_78>.

Last updated 2 months ago

automlbayesian-optimizationbbotkblack-box-optimizationgaussian-processhpohyperparameterhyperparameter-optimizationhyperparameter-tuningmachine-learningmlr3model-based-optimizationoptimizationoptimizerrandom-foresttuning

8.64 score 25 stars 3 dependents 113 scripts 2.9k downloads

mlr3spatiotempcv - Spatiotemporal Resampling Methods for 'mlr3'

Extends the mlr3 machine learning framework with spatio-temporal resampling methods to account for the presence of spatiotemporal autocorrelation (STAC) in predictor variables. STAC may cause highly biased performance estimates in cross-validation if ignored. A JSS article is available at <doi:10.18637/jss.v111.i07>.

Last updated 2 months ago

cross-validationmlr3resamplingresampling-methodsspatialtemporal

8.24 score 50 stars 123 scripts 706 downloads

mlr3verse - Easily Install and Load the 'mlr3' Package Family

The 'mlr3' package family is a set of packages for machine-learning purposes built in a modular fashion. This wrapper package is aimed to simplify the installation and loading of the core 'mlr3' packages. Get more information about the 'mlr3' project at <https://mlr3book.mlr-org.com/>.

Last updated 4 days ago

machine-learningmetamlr3

8.20 score 54 stars 1 dependents 716 scripts 2.3k downloads

mlr3cluster - Cluster Extension for 'mlr3'

Extends the 'mlr3' package with cluster analysis.

Last updated 4 months ago

cluster-analysisclusteringmlr3

8.12 score 23 stars 2 dependents 54 scripts 2.5k downloads

mlr3fselect - Feature Selection for 'mlr3'

Feature selection package of the 'mlr3' ecosystem. It selects the optimal feature set for any 'mlr3' learner. The package works with several optimization algorithms e.g. Random Search, Recursive Feature Elimination, and Genetic Search. Moreover, it can automatically optimize learners and estimate the performance of optimized feature sets with nested resampling.

Last updated 2 days ago

evolutionary-algorithmsexhaustive-searchfeature-selectionmachine-learningmlr3optimizationrandom-searchrecursive-feature-eliminationsequential-feature-selection

8.12 score 23 stars 2 dependents 69 scripts 2.7k downloads

mlr3filters - Filter Based Feature Selection for 'mlr3'

Extends 'mlr3' with filter methods for feature selection. Besides standalone filter methods built-in methods of any machine-learning algorithm are supported. Partial scoring of multivariate filter methods is supported.

Last updated 9 months ago

feature-selectionfilterfiltersmlrmlr3variable-importance

7.98 score 20 stars 3 dependents 95 scripts 3.1k downloads

mlr3proba - Probabilistic Supervised Learning for 'mlr3'

Provides extensions for probabilistic supervised learning for 'mlr3'. This includes extending the regression task to probabilistic and interval regression, adding a survival task, and other specialized models, predictions, and measures.

Last updated 11 days ago

density-estimationmachine-learningmlr3probabilistic-regressionprobabilistic-supervised-learningsupervised-learningsurvival-analysiscpp

7.89 score 134 stars 246 scripts 215 downloads

mlr3hyperband - Hyperband for 'mlr3'

Successive Halving (Jamieson and Talwalkar (2016) <doi:10.48550/arXiv.1502.07943>) and Hyperband (Li et al. 2018 <doi:10.48550/arXiv.1603.06560>) optimization algorithm for the mlr3 ecosystem. The implementation in mlr3hyperband features improved scheduling and parallelizes the evaluation of configurations. The package includes tuners for hyperparameter optimization in mlr3tuning and optimizers for black-box optimization in bbotk.

Last updated 7 months ago

automlbbotkhyperbandhyperparameter-tuningmachine-learningmlr3optimizationtunetuning

7.50 score 18 stars 3 dependents 44 scripts 2.0k downloads

mlr3torch - Deep Learning with 'mlr3'

Deep Learning library that extends the mlr3 framework by building upon the 'torch' package. It allows to conveniently build, train, and evaluate deep learning models without having to worry about low level details. Custom architectures can be created using the graph language defined in 'mlr3pipelines'.

Last updated 3 months ago

data-sciencedeep-learningmachine-learningmlr3torch

7.06 score 41 stars 49 scripts 580 downloads

mlr3spatial - Support for Spatial Objects Within the 'mlr3' Ecosystem

Extends the 'mlr3' ML framework with methods for spatial objects. Data storage and prediction are supported for packages 'terra', 'raster' and 'stars'.

Last updated 11 months ago

mlr3raster-predictionspatialspatial-modelling

6.90 score 43 stars 62 scripts 459 downloads

mlr3data - Collection of Machine Learning Data Sets for 'mlr3'

A small collection of interesting and educational machine learning data sets which are used as examples in the 'mlr3' book (<https://mlr3book.mlr-org.com>), the use case gallery (<https://mlr3gallery.mlr-org.com>), or in other examples. All data sets are properly preprocessed and ready to be analyzed by most machine learning algorithms. Data sets are automatically added to the dictionary of tasks if 'mlr3' is loaded.

Last updated 2 months ago

datadata-sciencedata-setsmachine-learningmlr3

5.28 score 2 stars 2 dependents 18 scripts 2.9k downloads

mlr3oml - Connector Between 'mlr3' and 'OpenML'

Provides an interface to 'OpenML.org' to list and download machine learning data, tasks and experiments. The 'OpenML' objects can be automatically converted to 'mlr3' objects. For a more sophisticated interface with more upload options, see the 'OpenML' package.

Last updated 8 months ago

datadata-sciencedatasetsmachine-learningmlr3openmlcpp

5.18 score 6 stars 102 scripts 797 downloads

mlr3benchmark - Analysis and Visualisation of Benchmark Experiments

Implements methods for post-hoc analysis and visualisation of benchmark experiments, for 'mlr3' and beyond.

Last updated 2 years ago

analysisbenchmark-analysisbenchmark-experimentsbenchmarkingmlr3

5.17 score 12 stars 49 scripts 534 downloads

mlr3fda - Extending 'mlr3' to Functional Data Analysis

Extends the 'mlr3' ecosystem to functional analysis by adding support for irregular and regular functional data as defined in the 'tf' package. The package provides 'PipeOps' for preprocessing functional columns and for extracting scalar features, thereby allowing standard machine learning algorithms to be applied afterwards. Available operations include simple functional features such as the mean or maximum, smoothing, interpolation, flattening, and functional 'PCA'.

Last updated 6 months ago

data-analysisdata-analysis-in-rdata-sciencefunctional-datamachine-learningmlr3

5.02 score 5 stars 5 scripts 277 downloads

rush - Rapid Parallel and Distributed Computing

Parallel computing with a network of local and remote workers. Fast exchange of results between the workers through a 'Redis' database. Key features include task queues, local caching, and sophisticated error handling.

Last updated 2 months ago

mlr3parallel-computing

4.88 score 10 stars 5 scripts 838 downloads

mlr3batchmark - Batch Experiments for 'mlr3'

Extends the 'mlr3' package with a connector to the package 'batchtools'. This allows to run large-scale benchmark experiments on scheduled high-performance computing clusters.

Last updated 1 years ago

batchtoolscluster-computinghigh-performance-computinghpcmlr3

4.84 score 5 stars 55 scripts 363 downloads

mlr3db - Data Base Backend for 'mlr3'

Extends the 'mlr3' package with a backend to transparently work with databases such as 'SQLite', 'DuckDB', 'MySQL', 'MariaDB', or 'PostgreSQL'. The package provides two additional backends: 'DataBackendDplyr' relies on the abstraction of package 'dbplyr' to interact with most DBMS. 'DataBackendDuckDB' operates on 'DuckDB' data bases and also on Apache Parquet files.

Last updated 1 years ago

bigquerydata-backenddatabaseduckdbmachine-learningmariadbmlr3mysqlodbcpostgresqlsparksqlite

4.73 score 21 stars 17 scripts 413 downloads

mlr3inferr - Inference on the Generalization Error

Confidence interval and resampling methods for inference on the generalization error.

Last updated 4 days ago

machine-learningstatistics

3.85 score 2 stars 3 scripts