Add regr.fuser learner (fused Lasso regression)#555
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EngineerDanny wants to merge 3 commits intomlr-org:mainfrom
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Add regr.fuser learner (fused Lasso regression)#555EngineerDanny wants to merge 3 commits intomlr-org:mainfrom
EngineerDanny wants to merge 3 commits intomlr-org:mainfrom
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be-marc
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Mar 20, 2026
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Hey, thanks for contributing. Lot of unnecessary checks. Otherwise, looks good to me. You need to release your fuser fork on r-universe; gh remotes do not work well for us.
| x = as_numeric_matrix(task$data(cols = feature_names)) | ||
| y = as.numeric(task$truth()) | ||
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| if (length(y) != nrow(x)) { |
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This check is superfluous. mlr3 guarantees this.
| stopf("Target length (%i) must match the number of rows (%i).", | ||
| length(y), nrow(x)) | ||
| } | ||
| if (anyNA(x) || anyNA(y)) { |
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This is also unnecessary. We check this in mlr3 when the learner does not have the property "missings".
| groups = as.character(groups) | ||
| } | ||
| groups = as.vector(groups) | ||
| if (length(groups) != nrow(x)) { |
| stopf("Grouping column length (%i) must match the number of rows (%i).", | ||
| length(groups), nrow(x)) | ||
| } | ||
| if (anyNA(groups)) { |
| } | ||
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| pv = self$param_set$get_values(tags = "train") | ||
| if (!is.null(pv$lambda) && (!is.numeric(pv$lambda) || length(pv$lambda) != 1L)) { |
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Guaranteed by the parameter set
| if (!is.null(pv$lambda) && (!is.numeric(pv$lambda) || length(pv$lambda) != 1L)) { | ||
| stopf("Parameter 'lambda' must be a numeric scalar or NULL.") | ||
| } | ||
| if (!is.numeric(pv$gamma) || length(pv$gamma) != 1L) { |
| stopf("Grouping column length (%i) must match the number of rows (%i).", | ||
| length(groups), nrow(x)) | ||
| } | ||
| if (anyNA(x)) { |
| } | ||
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| x = as_numeric_matrix(task$data(cols = self$model$feature_names)) | ||
| if (length(groups) != nrow(x)) { |
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I would suggest changing role name from group to subset.
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Summary
Adds a new regression learner
regr.fuserthat wraps the fused Lasso model fromfuserand requires a single grouping column via thegrouprole.Implementation Details
LearnerRegrFuserfuser::fusedL2DescentGLMNet(X, y, groups, lambda, G, gamma, scaling)grouprolelambda = NULL,gamma = 1,scaling = FALSE,G = NULL(defaults to all-ones K×K)lambda,gamma, andGdimensionsExample
Tests
Rscript -e 'testthat::test_file("tests/testthat/test_fuser_regr_fuser.R")'Notes
fuser(GitHub fork):remotes::install_github("EngineerDanny/fuser")Closes #426