Publications by Machine Learning in R
mlr wins Open Source Machine Learning Software Award
mlr receives Open Source Machine Learning Project Award mlr receives Open Source Machine Learning Project Award We’re extremely proud to have received the Open Source Machine Learning Project Award at ODSC West 2019. We were joined by Tensorflow, DataKind, and SHAP, which also received awards. The ODSC awards recognize projects that have made...
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useR 2020 tutorial on mlr3, mlr3tuning and pipelines
We would like to invite you to our useR 2020 tutorial on mlr3, mlr3tuning and mlr3pipelines taught by Bernd Bischl and Michel Lang. The tutorial will take place on 7th August at 10:00 (UTC-5). You can find more information and the registration link on meetup.com. Related ...
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useR 2020 tutorial on mlr3, mlr3tuning and pipelines
We would like to invite you to our useR 2020 tutorial on mlr3, mlr3tuning and mlr3pipelines taught by Bernd Bischl and Michel Lang. The tutorial will take place on 7th August at 10:00 (UTC-5). You can find more information and the registration link on meetup.com. Related To leave a comment for the author, please follow the link and comment on t...
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useR 2020 tutorial on mlr3, mlr3tuning and pipelines
We would like to invite you to our useR 2020 tutorial on mlr3, mlr3tuning and mlr3pipelines taught by Bernd Bischl and Michel Lang. The tutorial will take place on 7th August at 10:00 (UTC-5). You can find more information and the registration link on meetup.com. Related To leave a comment for the author, please follow the link and comment on t...
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Introducing mlr3cluster: Cluster Analysis Package
Tired of learning to use multiple packages to access clustering algorithms? Using different packages makes it difficult to compare the performance of clusterers? It would be great to have just one package that makes interfacing all things clustering easy? mlr3cluster to the rescue! mlr3cluster is a cluster analysis extention package within the mlr...
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Introducing mlr3cluster: Cluster Analysis Package
Tired of learning to use multiple packages to access clustering algorithms? Using different packages makes it difficult to compare the performance of clusterers? It would be great to have just one package that makes interfacing all things clustering easy? mlr3cluster to the rescue! mlr3cluster is a cluster analysis extention package within the ml...
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mlr3spatiotempcv: Initial CRAN release
We are happy to announce that a new extension package has joined the CRAN family of mlr3 packages. mlr3spatiotempcv was in the works for more than a year and adds spatiotemporal resampling methods to the mlr3 ecosystem. Such dedicated resampling methods make it possible to retrieve biased-reduced performance estimates in cross-validation scenario...
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mlr3spatiotempcv: Initial CRAN release
We are happy to announce that a new extension package has joined the CRAN family of mlr3 packages. mlr3spatiotempcv was in the works for more than a year and adds spatiotemporal resampling methods to the mlr3 ecosystem. Such dedicated resampling methods make it possible to retrieve biased-reduced performance estimates in cross-validation scenario...
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The Cross-Validation – Train/Predict misunderstanding
Introduction Over the past years I’ve seen multiple posts on Stackoverflow and our GitHub issues which suffer from a conceptual misunderstanding: cross-validation (CV) vs. train/predict. Because train/predict is an essential part of cross-validation, the point might not be so obvious. I’ll try to make it more clear by providing some exemplar...
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The “Cross-Validation – Train/Predict” misunderstanding
Introduction Over the past years I’ve seen multiple posts on Stackoverflow and our GitHub issues which suffer from a conceptual misunderstanding: cross-validation (CV) vs. train/predict. Because train/predict is an essential part of cross-validation, the point might not be so obvious. I’ll try to make it more clear by providing some exemplary...
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