From 1b28b2fd629bfb74697eaf57c44d393fd4aa64b0 Mon Sep 17 00:00:00 2001 From: Louis Aslett Date: Fri, 12 Sep 2025 16:13:21 +0100 Subject: [PATCH] Fix documentation "lost braces" NOTEs triggered by new CRAN checks as part of R Dev Day 2025 held at University of Warwick . Also fixed numerous other documentation errors flagged by `tools::checkRd`. --- R/MBOResult.R | 16 +++++----- R/OptProblem.R | 2 +- R/OptResult.R | 2 +- R/OptState.R | 2 +- R/SMBO.R | 2 +- R/doc_error_handling.R | 20 ++++++------- R/doc_mbo_OptPath.R | 8 ++--- R/doc_mbo_parallel.R | 6 ++-- R/exampleRun.R | 4 +-- R/exampleRunMultiObj.R | 2 +- R/getMBOInfillCrit.R | 2 +- R/getSupportedInfillOptFunctions.R | 2 +- R/getSupportedMultipointInfillOptFunctions.R | 2 +- R/infill_crits.R | 2 +- R/initCrit.R | 2 +- R/makeMBOControl.R | 6 ++-- R/makeMBOInfillCrit.R | 2 +- R/makeMBOLearner.R | 29 +++++++++---------- R/makeMBOTrafoFunction.R | 10 +++---- R/mbo.R | 2 +- R/mboContinue.R | 2 +- R/mboFinalize.R | 2 +- R/plotExampleRun.R | 2 +- R/renderExampleRunPlot.R | 2 +- R/setMBOControlInfill.R | 2 +- R/setMBOControlMultiObj.R | 7 +++-- R/setMBOControlMultiPoint.R | 2 +- R/setMBOControlTermination.R | 2 +- man/MBOInfillCrit.Rd | 2 +- man/MBOMultiObjResult.Rd | 8 ++--- man/MBOSingleObjResult.Rd | 8 ++--- man/OptProblem.Rd | 2 +- man/OptResult.Rd | 2 +- man/OptState.Rd | 2 +- man/error_handling.Rd | 20 ++++++------- man/exampleRun.Rd | 2 +- man/exampleRunMultiObj.Rd | 2 +- man/getGlobalOpt.Rd | 4 +-- man/getMBOInfillCrit.Rd | 2 +- man/getSupportedInfillOptFunctions.Rd | 2 +- ...etSupportedMultipointInfillOptFunctions.Rd | 2 +- man/infillcrits.Rd | 8 ++--- man/initCrit.Rd | 2 +- man/initSMBO.Rd | 2 +- man/makeMBOControl.Rd | 4 +-- man/makeMBOLearner.Rd | 29 +++++++++---------- man/makeMBOTrafoFunction.Rd | 2 +- man/mbo.Rd | 2 +- man/mboContinue.Rd | 2 +- man/mboFinalize.Rd | 2 +- man/mbo_OptPath.Rd | 8 ++--- man/mbo_parallel.Rd | 6 ++-- man/plotExampleRun.Rd | 2 +- man/print.MBOControl.Rd | 4 +-- man/renderExampleRunPlot.Rd | 2 +- man/setMBOControlInfill.Rd | 2 +- man/setMBOControlMultiObj.Rd | 7 +++-- man/setMBOControlMultiPoint.Rd | 2 +- man/setMBOControlTermination.Rd | 2 +- man/trafos.Rd | 8 ++--- 60 files changed, 149 insertions(+), 149 deletions(-) diff --git a/R/MBOResult.R b/R/MBOResult.R index 2498913bc..89a595cf4 100644 --- a/R/MBOResult.R +++ b/R/MBOResult.R @@ -1,8 +1,8 @@ -#' @title Single-Objective result object. +#' @title Single-Objective result object #' #' @description #' -#' \itemize{ +#' \describe{ #' \item{x [\code{list}]}{Named list of proposed optimal parameters.} #' \item{y [\code{numeric(1)}]}{Value of objective function at \code{x}, #' either from evals during optimization or from requested final evaluations, @@ -12,7 +12,7 @@ #' Includes all evaluated points and additional information as documented in \link{mbo_OptPath}. #' You can convert it via \code{as.data.frame}.} #' \item{resample.results [List of \code{\link[mlr]{ResampleResult}}]}{List of the desired \code{resample.results} if \code{resample.at} is set in \code{makeMBOControl}.} -#' \item{final.state [\code{character}] The final termination state. Gives information why the optimization ended. Possible values are +#' \item{final.state [\code{character}]}{The final termination state. Gives information why the optimization ended. Possible values are #' \describe{ #' \item{term.iter}{Maximal number of iterations reached.} #' \item{term.time}{Maximal running time exceeded.} @@ -23,7 +23,7 @@ #' } #' } #' \item{models [List of \code{\link[mlr]{WrappedModel}}]}{List of saved regression models if \code{store.model.at} is set in \code{makeMBOControl}. The default is that it contains the model generated after the last iteration.} -#' \item{control [\code{MBOControl}] Control object used in optimization} +#' \item{control [\code{MBOControl}]}{Control object used in optimization} #' } #' @name MBOSingleObjResult #' @rdname MBOSingleObjResult @@ -83,20 +83,20 @@ print.MBOResult = function(x, ...) { print(tail(as.data.frame(op), 10)) } -#' @title Multi-Objective result object. +#' @title Multi-Objective result object #' #' @description #' -#' \itemize{ +#' \describe{ #' \item{pareto.front [\code{matrix}]}{Pareto front of all evaluated points.} #' \item{pareto.set [\code{list} of \code{list}s]}{Pareto set of all evaluated points.} #' \item{pareto.inds [\code{numeric}]}{Indices of the Pareto-optimal points in the opt.path} #' \item{opt.path [\code{\link[ParamHelpers]{OptPath}}]}{Optimization path. #' Includes all evaluated points and additional information as documented in \link{mbo_OptPath}. #' You can convert it via \code{as.data.frame}.} -#' \item{final.state [\code{character}] The final termination state. Gives information why the optimization ended} +#' \item{final.state [\code{character}]}{The final termination state. Gives information why the optimization ended} #' \item{models [List of \code{\link[mlr]{WrappedModel}}]}{List of saved regression models.} -#' \item{control[\code{MBOControl}] Control object used in optimization} +#' \item{control[\code{MBOControl}]}{Control object used in optimization} #' } #' @name MBOMultiObjResult #' @rdname MBOMultiObjResult diff --git a/R/OptProblem.R b/R/OptProblem.R index c5ca42410..35d61a928 100644 --- a/R/OptProblem.R +++ b/R/OptProblem.R @@ -1,4 +1,4 @@ -#' @title OptProblem object. +#' @title OptProblem object #' @description #' The OptProblem contains all the constants values which define a OptProblem within our MBO Steps. #' It is an environment and is always pointed at by the OptState. diff --git a/R/OptResult.R b/R/OptResult.R index bbbd73b0a..e9f704ae1 100644 --- a/R/OptResult.R +++ b/R/OptResult.R @@ -1,4 +1,4 @@ -#' @title OptResult object. +#' @title OptResult object #' @description #' The OptResult stores all entities which are not needed while optimizing but are needed to build the final result. #' It can contains fitted surrogate models at certain times as well as resample objects. diff --git a/R/OptState.R b/R/OptState.R index 517739a82..951c9131f 100644 --- a/R/OptState.R +++ b/R/OptState.R @@ -1,4 +1,4 @@ -#' @title OptState object. +#' @title OptState object #' @description #' The OptState is the central component of the mbo iterations. #' This environment contains every necessary information needed during optimization in MBO. diff --git a/R/SMBO.R b/R/SMBO.R index 9937fb228..6c698787a 100644 --- a/R/SMBO.R +++ b/R/SMBO.R @@ -1,4 +1,4 @@ -#' @title Initialize a manual sequential MBO run. +#' @title Initialize a manual sequential MBO run #' @description When you want to run a human-in-the-loop MBO run you need to initialize it first. #' #' @inheritParams mbo diff --git a/R/doc_error_handling.R b/R/doc_error_handling.R index da285dcb4..f518c9de8 100644 --- a/R/doc_error_handling.R +++ b/R/doc_error_handling.R @@ -5,17 +5,17 @@ #' process. mlrMBO tries to handle most of them as smart as possible. #' #' The target function could -#' \itemize{ -#' \item{1}{The target function returns NA(s) or NaN(s) (plural for the multi-objective case).} -#' \item{2}{The target function stops with an error.} -#' \item{3}{The target function does not return at all (infinite or very long execution time).} -#' \item{4}{The target function crashes the whole R process.} -#' \item{5}{The surrogate machine learning model might crash. -#' Kriging quite often can run into numerical problems.} -#' \item{6}{The proposal mechanism - in multi-point or single point mode - produces +#' \enumerate{ +#' \item The target function returns NA(s) or NaN(s) (plural for the multi-objective case). +#' \item The target function stops with an error. +#' \item The target function does not return at all (infinite or very long execution time). +#' \item The target function crashes the whole R process. +#' \item The surrogate machine learning model might crash. +#' Kriging quite often can run into numerical problems. +#' \item The proposal mechanism - in multi-point or single point mode - produces #' a point which is either close to another candidate point in the same iteration or -#' an already visited point in a previous iteration.} -#' \item{7}{The mbo process exits / stops / crashes itself. Maybe because it hit a walltime.} +#' an already visited point in a previous iteration. +#' \item The mbo process exits / stops / crashes itself. Maybe because it hit a walltime. #' } #' #' diff --git a/R/doc_mbo_OptPath.R b/R/doc_mbo_OptPath.R index 5a07326e8..4ec5fab7e 100644 --- a/R/doc_mbo_OptPath.R +++ b/R/doc_mbo_OptPath.R @@ -11,10 +11,10 @@ #' \item{prop.type}{Type of point proposal. Possible values are #' \describe{ #' \item{initdesign}{Points actually not proposed, but in the initial design.} -#' \item{infill\_x}{Here x is a placeholder for the selected infill criterion, e.g., infill\_ei for expected improvement.} -#' \item{random\_interleave}{Uniformly sampled points added additionally to the proposed points.} -#' \item{random\_filtered}{If filtering of proposed points located too close to each other is active, these are replaced by random points.} -#' \item{final\_eval}{If \code{final.evals} is set in \code{\link{makeMBOControl}}: Final evaluations of the proposed solution to reduce noise in y.} +#' \item{infill_x}{Here x is a placeholder for the selected infill criterion, e.g., infill_ei for expected improvement.} +#' \item{random_interleave}{Uniformly sampled points added additionally to the proposed points.} +#' \item{random_filtered}{If filtering of proposed points located too close to each other is active, these are replaced by random points.} +#' \item{final_eval}{If \code{final.evals} is set in \code{\link{makeMBOControl}}: Final evaluations of the proposed solution to reduce noise in y.} #' } #' } #' \item{parego.weight}{Weight vector sampled for multi-point ParEGO} diff --git a/R/doc_mbo_parallel.R b/R/doc_mbo_parallel.R index 36dc13e8d..e8201c6c6 100644 --- a/R/doc_mbo_parallel.R +++ b/R/doc_mbo_parallel.R @@ -2,7 +2,7 @@ #' #' @description #' In mlrMBO you can parallelize the tuning on two different levels to speed up computation: -#' \itemize{ +#' \describe{ #' \item{\code{mlrMBO.feval}}{Multiple evaluations of the target function.} #' \item{\code{mlrMBO.propose.points}}{Optimization of the infill criteria if multiple are used (e.g. ParEGO and ParallelLCB)} #' } @@ -11,8 +11,8 @@ #' The different levels of parallelization can be specified in \code{parallelStart*}. #' Details for the levels mentioned above are given below: #' \itemize{ -#' \item{Evaluation of the objective function can be parallelized in cases multiple points are to be evaluated at once. These are: evaluation of the initial design, multiple proposed points per iteration and evaluation of the target function in \code{\link{exampleRun}}. (Level: \code{mlrMBO.feval})} -#' \item{Model fitting / point proposal - in some cases where independent, expensive operations are performed. (Level: \code{mlrMBO.propose.points})} +#' \item Evaluation of the objective function can be parallelized in cases multiple points are to be evaluated at once. These are: evaluation of the initial design, multiple proposed points per iteration and evaluation of the target function in \code{\link{exampleRun}}. (Level: \code{mlrMBO.feval}) +#' \item Model fitting / point proposal - in some cases where independent, expensive operations are performed. (Level: \code{mlrMBO.propose.points}) #' } #' Details regarding the latter: #' \describe{ diff --git a/R/exampleRun.R b/R/exampleRun.R index 0514b87d3..5167fe069 100644 --- a/R/exampleRun.R +++ b/R/exampleRun.R @@ -1,4 +1,4 @@ -#' @title Perform an mbo run on a test function and and visualize what happens. +#' @title Perform an mbo run on a test function and and visualize what happens #' #' @description #' Usually used for 1D or 2D examples, @@ -164,7 +164,7 @@ evaluate = function(fun, par.set, n.params, par.types, noisy, noisy.evals, point } } -#' Helper function which returns the (estimated) global optimum. +#' Helper function which returns the (estimated) global optimum #' #' @param run [\code{MBOExampleRun}]\cr #' Object of type \code{MBOExampleRun}. diff --git a/R/exampleRunMultiObj.R b/R/exampleRunMultiObj.R index 33b9eb658..a3e1f0170 100644 --- a/R/exampleRunMultiObj.R +++ b/R/exampleRunMultiObj.R @@ -1,4 +1,4 @@ -#' @title Perform an MBO run on a multi-objective test function and and visualize what happens. +#' @title Perform an MBO run on a multi-objective test function and and visualize what happens #' #' @description #' Only available for 2D -> 2D examples, diff --git a/R/getMBOInfillCrit.R b/R/getMBOInfillCrit.R index d68146fc8..59da60b97 100644 --- a/R/getMBOInfillCrit.R +++ b/R/getMBOInfillCrit.R @@ -1,4 +1,4 @@ -#' @title Get properties of MBO infill criterion. +#' @title Get properties of MBO infill criterion #' #' @description #' Returns properties of an infill criterion, e.g., name or id. diff --git a/R/getSupportedInfillOptFunctions.R b/R/getSupportedInfillOptFunctions.R index 4c007190e..6861331fd 100644 --- a/R/getSupportedInfillOptFunctions.R +++ b/R/getSupportedInfillOptFunctions.R @@ -1,4 +1,4 @@ -#' @title Get names of supported infill-criteria optimizers. +#' @title Get names of supported infill-criteria optimizers #' @description #' None. #' @return [\code{character}] diff --git a/R/getSupportedMultipointInfillOptFunctions.R b/R/getSupportedMultipointInfillOptFunctions.R index f701e85e3..af5e8bc6b 100644 --- a/R/getSupportedMultipointInfillOptFunctions.R +++ b/R/getSupportedMultipointInfillOptFunctions.R @@ -1,4 +1,4 @@ -#' @title Get names of supported multi-point infill-criteria optimizers. +#' @title Get names of supported multi-point infill-criteria optimizers #' #' @description #' Returns all names of supported multi-point infill-criteria optimizers. diff --git a/R/infill_crits.R b/R/infill_crits.R index cab9aa7b5..8bf729664 100644 --- a/R/infill_crits.R +++ b/R/infill_crits.R @@ -1,4 +1,4 @@ -#' @title Infill criteria. +#' @title Infill criteria #' #' @description #' \pkg{mlrMBO} contains most of the most popular infill criteria, e.g., expected diff --git a/R/initCrit.R b/R/initCrit.R index c94393e46..61953516a 100644 --- a/R/initCrit.R +++ b/R/initCrit.R @@ -1,4 +1,4 @@ -#' @title Initialize an MBO infill criterion. +#' @title Initialize an MBO infill criterion #' #' @description #' Some infill criteria have parameters that are dependent on values in the parameter set, design, diff --git a/R/makeMBOControl.R b/R/makeMBOControl.R index b0bfa8541..c1d8f629b 100644 --- a/R/makeMBOControl.R +++ b/R/makeMBOControl.R @@ -1,4 +1,4 @@ -#' @title Set MBO options. +#' @title Set MBO options #' #' @description #' Creates a control object for MBO optimization. @@ -78,7 +78,7 @@ #' Possible values are: #' \dQuote{stop}: R exception is generated. #' \dQuote{warn}: The error will be converted to a waring and a random point will be proposed. -#' \dQuote{quiet}: Same as “warn” but without the warning. +#' \dQuote{quiet}: Same as "warn" but without the warning. #' This will overwrite the mlr setting \code{on.learner.error} for the surrogate learner. #' Default is: \dQuote{stop}. #' @@ -165,7 +165,7 @@ makeMBOControl = function(n.objectives = 1L, return(control) } -#' Print mbo control object. +#' Print mbo control object #' #' @param x [\code{\link{MBOControl}}]\cr #' Control object. diff --git a/R/makeMBOInfillCrit.R b/R/makeMBOInfillCrit.R index 35c1a51a9..a3d11aa95 100644 --- a/R/makeMBOInfillCrit.R +++ b/R/makeMBOInfillCrit.R @@ -1,4 +1,4 @@ -#' @title Create an infill criterion. +#' @title Create an infill criterion #' #' @description The infill criterion guides the model based search process. #' The most prominent infill criteria, e.g., expected improvement, lower diff --git a/R/makeMBOLearner.R b/R/makeMBOLearner.R index 4a58c8494..8b8784ca8 100644 --- a/R/makeMBOLearner.R +++ b/R/makeMBOLearner.R @@ -1,4 +1,4 @@ -#' @title Generate default learner. +#' @title Generate default learner #' #' @description #' This is a helper function that generates a default surrogate, based on properties of the objective @@ -6,39 +6,38 @@ #' #' For numeric-only (including integers) parameter spaces without any dependencies: #' \itemize{ -#' \item{A Kriging model \dQuote{regr.km} with kernel \dQuote{matern3_2} is created.} -#' \item{If the objective function is deterministic we add a small nugget effect (10^-8*Var(y), +#' \item A Kriging model \dQuote{regr.km} with kernel \dQuote{matern3_2} is created. +#' \item If the objective function is deterministic we add a small nugget effect (10^-8*Var(y), #' y is vector of observed outcomes in current design) to increase numerical stability to -#' hopefully prevent crashes of DiceKriging.} -#' \item{If the objective function is noisy the nugget effect will be estimated with -#' \code{nugget.estim = TRUE} (but you can override this in \code{...}.} +#' hopefully prevent crashes of DiceKriging. +#' \item If the objective function is noisy the nugget effect will be estimated with +#' \code{nugget.estim = TRUE} (but you can override this in \code{...}. #' Also \code{jitter} is set to \code{TRUE} to circumvent a problem with DiceKriging where already #' trained input values produce the exact trained output. #' For further information check the \code{$note} slot of the created learner. -#' \item{Instead of the default \code{"BFGS"} optimization method we use rgenoud (\code{"gen"}), +#' \item Instead of the default \code{"BFGS"} optimization method we use rgenoud (\code{"gen"}), #' which is a hybrid algorithm, to combine global search based on genetic algorithms and local search #' based on gradients. #' This may improve the model fit and will less frequently produce a constant surrogate model. -#' You can also override this setting in \code{...}.} +#' You can also override this setting in \code{...}. #' } #' #' For mixed numeric-categorical parameter spaces, or spaces with conditional parameters: #' \itemize{ -#' \item{A random regression forest \dQuote{regr.randomForest} with 500 trees is created.} -#' \item{The standard error of a prediction (if required by the infill criterion) is estimated +#' \item A random regression forest \dQuote{regr.randomForest} with 500 trees is created. +#' \item The standard error of a prediction (if required by the infill criterion) is estimated #' by computing the jackknife-after-bootstrap. #' This is the \code{se.method = "jackknife"} option of the \dQuote{regr.randomForest} Learner. -#' } #' } #' #' If additionally dependencies are in present in the parameter space, inactive conditional parameters #' are represented by missing \code{NA} values in the training design data.frame. #' We simply handle those with an imputation method, added to the random forest: #' \itemize{ -#' \item{If a numeric value is inactive, i.e., missing, it will be imputed by 2 times the -#' maximum of observed values} -#' \item{If a categorical value is inactive, i.e., missing, it will be imputed by the -#' special class label \code{"__miss__"}} +#' \item If a numeric value is inactive, i.e., missing, it will be imputed by 2 times the +#' maximum of observed values +#' \item If a categorical value is inactive, i.e., missing, it will be imputed by the +#' special class label \code{"__miss__"} #' } #' Both of these techniques make sense for tree-based methods and are usually hard to beat, see #' Ding et.al. (2010). diff --git a/R/makeMBOTrafoFunction.R b/R/makeMBOTrafoFunction.R index c270ce7f4..ef4c820de 100644 --- a/R/makeMBOTrafoFunction.R +++ b/R/makeMBOTrafoFunction.R @@ -1,4 +1,4 @@ -#' @title Create a transformation function for MBOExampleRun. +#' @title Create a transformation function for MBOExampleRun #' #' @description #' Creates a transformation function for MBOExampleRun. @@ -17,11 +17,11 @@ makeMBOTrafoFunction = function(name, fun) { return(fun) } -#' Transformation methods. +#' Transformation methods #' -#' \itemize{ -#' \item{\bold{logTrafo}}{\cr Natural logarithm.} -#' \item{\bold{sqrtTrafo}}{\cr Square root.} +#' \describe{ +#' \item{\bold{logTrafo}}{Natural logarithm.} +#' \item{\bold{sqrtTrafo}}{Square root.} #' } #' If negative values occur and the trafo function can handle only positive values, #' a shift of the form x - min(x) + 1 is performed prior to the transformation if the diff --git a/R/mbo.R b/R/mbo.R index 583bbeffa..a1a7f2e67 100644 --- a/R/mbo.R +++ b/R/mbo.R @@ -1,4 +1,4 @@ -#' @title Optimizes a function with sequential model based optimization. +#' @title Optimizes a function with sequential model based optimization #' #' @description #' See \link{mbo_parallel} for all parallelization options. diff --git a/R/mboContinue.R b/R/mboContinue.R index dc0c8e4eb..d705eddab 100644 --- a/R/mboContinue.R +++ b/R/mboContinue.R @@ -1,4 +1,4 @@ -#' @title Continues an mbo run from a save-file. +#' @title Continues an mbo run from a save-file #' #' @description #' Useful if your optimization is likely to crash, diff --git a/R/mboFinalize.R b/R/mboFinalize.R index cd4ce3555..07f8a78e0 100644 --- a/R/mboFinalize.R +++ b/R/mboFinalize.R @@ -1,4 +1,4 @@ -#' @title Finalizes an mbo run from a save-file. +#' @title Finalizes an mbo run from a save-file #' #' @description #' Useful if your optimization didn't terminate but you want a results nonetheless. diff --git a/R/plotExampleRun.R b/R/plotExampleRun.R index 928367b5d..a1003b8c6 100644 --- a/R/plotExampleRun.R +++ b/R/plotExampleRun.R @@ -1,4 +1,4 @@ -#' @title Renders plots for exampleRun objects and displays them. +#' @title Renders plots for exampleRun objects and displays them #' #' @description #' The graphical output depends on the target function at hand. diff --git a/R/renderExampleRunPlot.R b/R/renderExampleRunPlot.R index da882d706..e45413a33 100644 --- a/R/renderExampleRunPlot.R +++ b/R/renderExampleRunPlot.R @@ -1,5 +1,5 @@ #' @title Renders plots for exampleRun objects, either in 1D or 2D, or -#' exampleRunMultiObj objects. +#' exampleRunMultiObj objects #' #' @description #' The graphical output depends on the target function at hand. diff --git a/R/setMBOControlInfill.R b/R/setMBOControlInfill.R index cfd2cc749..81f5949a3 100644 --- a/R/setMBOControlInfill.R +++ b/R/setMBOControlInfill.R @@ -1,4 +1,4 @@ -#' @title Extends mbo control object with infill criteria and infill optimizer options. +#' @title Extends mbo control object with infill criteria and infill optimizer options #' #' @description #' Please note that internally all infill criteria are minimized. So for some of them, diff --git a/R/setMBOControlMultiObj.R b/R/setMBOControlMultiObj.R index 4adceaf05..1683c2089 100644 --- a/R/setMBOControlMultiObj.R +++ b/R/setMBOControlMultiObj.R @@ -1,6 +1,6 @@ #FIXME: briefly explain multi-point proposal for all three methods -#' @title Set multi-objective options. +#' @title Set multi-objective options #' @description #' Extends MBO control object with multi-objective specific options. #' @@ -60,6 +60,7 @@ #' @references #' For more information on the implemented multi-objective procedures the following #' sources might be helpful: +#' #' Knowles, J.: ParEGO: A hybrid algorithm with on-line landscape #' approximation for expensive multiobjective optimization problems. IEEE #' Transactions on Evolutionary Computation, 10 (2006) 1, pp. 50-66 @@ -83,8 +84,8 @@ #' 7th International. Conf. Evolutionary Multi-Criterion Optimization (EMO #' 2013), March 19-22, Sheffield, UK, R. Purshouse; P. J. Fleming; #' C. M. Fonseca; S. Greco; J. Shaw, eds., 2013, vol. 7811 of Lecture -#' Notes in Computer Science, ISBN 978-3-642-37139-4, pp. 756{770, -#' doi:10.1007/978-3-642-37140-0 56} +#' Notes in Computer Science, ISBN 978-3-642-37139-4, pp. 756-770, +#' doi:10.1007/978-3-642-37140-0 56 #' #' Jeong, S.; Obayashi, S.: Efficient global optimization (EGO) for Multi-Objective Problem and Data Mining. #' In: Proc. IEEE Congress on diff --git a/R/setMBOControlMultiPoint.R b/R/setMBOControlMultiPoint.R index 2c8313bbf..32ddaec20 100644 --- a/R/setMBOControlMultiPoint.R +++ b/R/setMBOControlMultiPoint.R @@ -1,4 +1,4 @@ -#' @title Set multipoint proposal options. +#' @title Set multipoint proposal options #' @description #' Extends an MBO control object with options for multipoint proposal. #' @template arg_control diff --git a/R/setMBOControlTermination.R b/R/setMBOControlTermination.R index 8f3c85fe8..be6606d0b 100644 --- a/R/setMBOControlTermination.R +++ b/R/setMBOControlTermination.R @@ -1,4 +1,4 @@ -#' @title Set termination options. +#' @title Set termination options #' #' @description #' Extends an MBO control object with infill criteria and infill optimizer options. diff --git a/man/MBOInfillCrit.Rd b/man/MBOInfillCrit.Rd index 2dd8d9f16..21de89b20 100644 --- a/man/MBOInfillCrit.Rd +++ b/man/MBOInfillCrit.Rd @@ -12,7 +12,7 @@ \alias{crit.aei} \alias{crit.eqi} \alias{crit.dib1} -\title{Create an infill criterion.} +\title{Create an infill criterion} \usage{ makeMBOInfillCrit( fun, diff --git a/man/MBOMultiObjResult.Rd b/man/MBOMultiObjResult.Rd index 0163f9426..51974b791 100644 --- a/man/MBOMultiObjResult.Rd +++ b/man/MBOMultiObjResult.Rd @@ -2,17 +2,17 @@ % Please edit documentation in R/MBOResult.R \name{MBOMultiObjResult} \alias{MBOMultiObjResult} -\title{Multi-Objective result object.} +\title{Multi-Objective result object} \description{ -\itemize{ +\describe{ \item{pareto.front [\code{matrix}]}{Pareto front of all evaluated points.} \item{pareto.set [\code{list} of \code{list}s]}{Pareto set of all evaluated points.} \item{pareto.inds [\code{numeric}]}{Indices of the Pareto-optimal points in the opt.path} \item{opt.path [\code{\link[ParamHelpers]{OptPath}}]}{Optimization path. Includes all evaluated points and additional information as documented in \link{mbo_OptPath}. You can convert it via \code{as.data.frame}.} - \item{final.state [\code{character}] The final termination state. Gives information why the optimization ended} + \item{final.state [\code{character}]}{The final termination state. Gives information why the optimization ended} \item{models [List of \code{\link[mlr]{WrappedModel}}]}{List of saved regression models.} - \item{control[\code{MBOControl}] Control object used in optimization} + \item{control[\code{MBOControl}]}{Control object used in optimization} } } diff --git a/man/MBOSingleObjResult.Rd b/man/MBOSingleObjResult.Rd index 93be51248..a7e31fd48 100644 --- a/man/MBOSingleObjResult.Rd +++ b/man/MBOSingleObjResult.Rd @@ -2,9 +2,9 @@ % Please edit documentation in R/MBOResult.R \name{MBOSingleObjResult} \alias{MBOSingleObjResult} -\title{Single-Objective result object.} +\title{Single-Objective result object} \description{ -\itemize{ +\describe{ \item{x [\code{list}]}{Named list of proposed optimal parameters.} \item{y [\code{numeric(1)}]}{Value of objective function at \code{x}, either from evals during optimization or from requested final evaluations, @@ -14,7 +14,7 @@ Includes all evaluated points and additional information as documented in \link{mbo_OptPath}. You can convert it via \code{as.data.frame}.} \item{resample.results [List of \code{\link[mlr]{ResampleResult}}]}{List of the desired \code{resample.results} if \code{resample.at} is set in \code{makeMBOControl}.} - \item{final.state [\code{character}] The final termination state. Gives information why the optimization ended. Possible values are + \item{final.state [\code{character}]}{The final termination state. Gives information why the optimization ended. Possible values are \describe{ \item{term.iter}{Maximal number of iterations reached.} \item{term.time}{Maximal running time exceeded.} @@ -25,6 +25,6 @@ } } \item{models [List of \code{\link[mlr]{WrappedModel}}]}{List of saved regression models if \code{store.model.at} is set in \code{makeMBOControl}. The default is that it contains the model generated after the last iteration.} - \item{control [\code{MBOControl}] Control object used in optimization} + \item{control [\code{MBOControl}]}{Control object used in optimization} } } diff --git a/man/OptProblem.Rd b/man/OptProblem.Rd index 174fbc157..a8ab70541 100644 --- a/man/OptProblem.Rd +++ b/man/OptProblem.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/OptProblem.R \name{OptProblem} \alias{OptProblem} -\title{OptProblem object.} +\title{OptProblem object} \description{ The OptProblem contains all the constants values which define a OptProblem within our MBO Steps. It is an environment and is always pointed at by the OptState. diff --git a/man/OptResult.Rd b/man/OptResult.Rd index e75df8241..047cea352 100644 --- a/man/OptResult.Rd +++ b/man/OptResult.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/OptResult.R \name{OptResult} \alias{OptResult} -\title{OptResult object.} +\title{OptResult object} \description{ The OptResult stores all entities which are not needed while optimizing but are needed to build the final result. It can contains fitted surrogate models at certain times as well as resample objects. diff --git a/man/OptState.Rd b/man/OptState.Rd index d7889dfca..b74d9484e 100644 --- a/man/OptState.Rd +++ b/man/OptState.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/OptState.R \name{OptState} \alias{OptState} -\title{OptState object.} +\title{OptState object} \description{ The OptState is the central component of the mbo iterations. This environment contains every necessary information needed during optimization in MBO. diff --git a/man/error_handling.Rd b/man/error_handling.Rd index a46450d81..aac4159ba 100644 --- a/man/error_handling.Rd +++ b/man/error_handling.Rd @@ -8,17 +8,17 @@ There are multiple types of errors that can occur during one optimization process. mlrMBO tries to handle most of them as smart as possible. The target function could -\itemize{ - \item{1}{The target function returns NA(s) or NaN(s) (plural for the multi-objective case).} - \item{2}{The target function stops with an error.} - \item{3}{The target function does not return at all (infinite or very long execution time).} - \item{4}{The target function crashes the whole R process.} - \item{5}{The surrogate machine learning model might crash. - Kriging quite often can run into numerical problems.} - \item{6}{The proposal mechanism - in multi-point or single point mode - produces +\enumerate{ + \item The target function returns NA(s) or NaN(s) (plural for the multi-objective case). + \item The target function stops with an error. + \item The target function does not return at all (infinite or very long execution time). + \item The target function crashes the whole R process. + \item The surrogate machine learning model might crash. + Kriging quite often can run into numerical problems. + \item The proposal mechanism - in multi-point or single point mode - produces a point which is either close to another candidate point in the same iteration or - an already visited point in a previous iteration.} - \item{7}{The mbo process exits / stops / crashes itself. Maybe because it hit a walltime.} + an already visited point in a previous iteration. + \item The mbo process exits / stops / crashes itself. Maybe because it hit a walltime. } diff --git a/man/exampleRun.Rd b/man/exampleRun.Rd index f639bf27a..ce283d525 100644 --- a/man/exampleRun.Rd +++ b/man/exampleRun.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/exampleRun.R \name{exampleRun} \alias{exampleRun} -\title{Perform an mbo run on a test function and and visualize what happens.} +\title{Perform an mbo run on a test function and and visualize what happens} \usage{ exampleRun( fun, diff --git a/man/exampleRunMultiObj.Rd b/man/exampleRunMultiObj.Rd index 912d11edb..7cbfc0a28 100644 --- a/man/exampleRunMultiObj.Rd +++ b/man/exampleRunMultiObj.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/exampleRunMultiObj.R \name{exampleRunMultiObj} \alias{exampleRunMultiObj} -\title{Perform an MBO run on a multi-objective test function and and visualize what happens.} +\title{Perform an MBO run on a multi-objective test function and and visualize what happens} \usage{ exampleRunMultiObj( fun, diff --git a/man/getGlobalOpt.Rd b/man/getGlobalOpt.Rd index 112352d7d..36f6c74ec 100644 --- a/man/getGlobalOpt.Rd +++ b/man/getGlobalOpt.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/exampleRun.R \name{getGlobalOpt} \alias{getGlobalOpt} -\title{Helper function which returns the (estimated) global optimum.} +\title{Helper function which returns the (estimated) global optimum} \usage{ getGlobalOpt(run) } @@ -14,5 +14,5 @@ Object of type \code{MBOExampleRun}.} [\code{numeric(1)}]. (Estimated) global optimum. } \description{ -Helper function which returns the (estimated) global optimum. +Helper function which returns the (estimated) global optimum } diff --git a/man/getMBOInfillCrit.Rd b/man/getMBOInfillCrit.Rd index 07b04ba90..e7ce1ec87 100644 --- a/man/getMBOInfillCrit.Rd +++ b/man/getMBOInfillCrit.Rd @@ -8,7 +8,7 @@ \alias{getMBOInfillCritId} \alias{hasRequiresInfillCritStandardError} \alias{getMBOInfillCritComponents} -\title{Get properties of MBO infill criterion.} +\title{Get properties of MBO infill criterion} \usage{ getMBOInfillCritParams(x) diff --git a/man/getSupportedInfillOptFunctions.Rd b/man/getSupportedInfillOptFunctions.Rd index e770d6c58..4f5056ab2 100644 --- a/man/getSupportedInfillOptFunctions.Rd +++ b/man/getSupportedInfillOptFunctions.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/getSupportedInfillOptFunctions.R \name{getSupportedInfillOptFunctions} \alias{getSupportedInfillOptFunctions} -\title{Get names of supported infill-criteria optimizers.} +\title{Get names of supported infill-criteria optimizers} \usage{ getSupportedInfillOptFunctions() } diff --git a/man/getSupportedMultipointInfillOptFunctions.Rd b/man/getSupportedMultipointInfillOptFunctions.Rd index e497e422e..d295f326b 100644 --- a/man/getSupportedMultipointInfillOptFunctions.Rd +++ b/man/getSupportedMultipointInfillOptFunctions.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/getSupportedMultipointInfillOptFunctions.R \name{getSupportedMultipointInfillOptFunctions} \alias{getSupportedMultipointInfillOptFunctions} -\title{Get names of supported multi-point infill-criteria optimizers.} +\title{Get names of supported multi-point infill-criteria optimizers} \usage{ getSupportedMultipointInfillOptFunctions() } diff --git a/man/infillcrits.Rd b/man/infillcrits.Rd index 769e31d29..7266ddd4f 100644 --- a/man/infillcrits.Rd +++ b/man/infillcrits.Rd @@ -10,19 +10,19 @@ \alias{makeMBOInfillCritEQI} \alias{makeMBOInfillCritDIB} \alias{makeMBOInfillCritAdaCB} -\title{Infill criteria.} +\title{Infill criteria} \usage{ makeMBOInfillCritMeanResponse() makeMBOInfillCritStandardError() -makeMBOInfillCritEI(se.threshold = 0.000001) +makeMBOInfillCritEI(se.threshold = 1e-06) makeMBOInfillCritCB(cb.lambda = NULL) -makeMBOInfillCritAEI(aei.use.nugget = FALSE, se.threshold = 0.000001) +makeMBOInfillCritAEI(aei.use.nugget = FALSE, se.threshold = 1e-06) -makeMBOInfillCritEQI(eqi.beta = 0.75, se.threshold = 0.000001) +makeMBOInfillCritEQI(eqi.beta = 0.75, se.threshold = 1e-06) makeMBOInfillCritDIB(cb.lambda = 1, sms.eps = NULL) diff --git a/man/initCrit.Rd b/man/initCrit.Rd index 36009f728..3d8b6d9ed 100644 --- a/man/initCrit.Rd +++ b/man/initCrit.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/initCrit.R \name{initCrit} \alias{initCrit} -\title{Initialize an MBO infill criterion.} +\title{Initialize an MBO infill criterion} \usage{ initCrit(crit, fun, design, learner, control) } diff --git a/man/initSMBO.Rd b/man/initSMBO.Rd index 993ab644a..675163d57 100644 --- a/man/initSMBO.Rd +++ b/man/initSMBO.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/SMBO.R \name{initSMBO} \alias{initSMBO} -\title{Initialize a manual sequential MBO run.} +\title{Initialize a manual sequential MBO run} \usage{ initSMBO( par.set, diff --git a/man/makeMBOControl.Rd b/man/makeMBOControl.Rd index aa1dca850..42761ccff 100644 --- a/man/makeMBOControl.Rd +++ b/man/makeMBOControl.Rd @@ -3,7 +3,7 @@ \name{makeMBOControl} \alias{makeMBOControl} \alias{MBOControl} -\title{Set MBO options.} +\title{Set MBO options} \usage{ makeMBOControl( n.objectives = 1L, @@ -117,7 +117,7 @@ What should happen when the surrogate learner can not train the model. Possible values are: \dQuote{stop}: R exception is generated. \dQuote{warn}: The error will be converted to a waring and a random point will be proposed. -\dQuote{quiet}: Same as “warn” but without the warning. +\dQuote{quiet}: Same as "warn" but without the warning. This will overwrite the mlr setting \code{on.learner.error} for the surrogate learner. Default is: \dQuote{stop}.} } diff --git a/man/makeMBOLearner.Rd b/man/makeMBOLearner.Rd index 3595d279f..6916fe26b 100644 --- a/man/makeMBOLearner.Rd +++ b/man/makeMBOLearner.Rd @@ -3,7 +3,7 @@ \name{makeMBOLearner} \alias{makeMBOLearner} \alias{mbo_default_learner} -\title{Generate default learner.} +\title{Generate default learner} \usage{ makeMBOLearner(control, fun, config = list(), ...) } @@ -30,39 +30,38 @@ function and the selected infill criterion. For numeric-only (including integers) parameter spaces without any dependencies: \itemize{ -\item{A Kriging model \dQuote{regr.km} with kernel \dQuote{matern3_2} is created.} -\item{If the objective function is deterministic we add a small nugget effect (10^-8*Var(y), +\item A Kriging model \dQuote{regr.km} with kernel \dQuote{matern3_2} is created. +\item If the objective function is deterministic we add a small nugget effect (10^-8*Var(y), y is vector of observed outcomes in current design) to increase numerical stability to - hopefully prevent crashes of DiceKriging.} -\item{If the objective function is noisy the nugget effect will be estimated with - \code{nugget.estim = TRUE} (but you can override this in \code{...}.} + hopefully prevent crashes of DiceKriging. +\item If the objective function is noisy the nugget effect will be estimated with + \code{nugget.estim = TRUE} (but you can override this in \code{...}. Also \code{jitter} is set to \code{TRUE} to circumvent a problem with DiceKriging where already trained input values produce the exact trained output. For further information check the \code{$note} slot of the created learner. -\item{Instead of the default \code{"BFGS"} optimization method we use rgenoud (\code{"gen"}), +\item Instead of the default \code{"BFGS"} optimization method we use rgenoud (\code{"gen"}), which is a hybrid algorithm, to combine global search based on genetic algorithms and local search based on gradients. This may improve the model fit and will less frequently produce a constant surrogate model. - You can also override this setting in \code{...}.} + You can also override this setting in \code{...}. } For mixed numeric-categorical parameter spaces, or spaces with conditional parameters: \itemize{ -\item{A random regression forest \dQuote{regr.randomForest} with 500 trees is created.} -\item{The standard error of a prediction (if required by the infill criterion) is estimated +\item A random regression forest \dQuote{regr.randomForest} with 500 trees is created. +\item The standard error of a prediction (if required by the infill criterion) is estimated by computing the jackknife-after-bootstrap. This is the \code{se.method = "jackknife"} option of the \dQuote{regr.randomForest} Learner. - } } If additionally dependencies are in present in the parameter space, inactive conditional parameters are represented by missing \code{NA} values in the training design data.frame. We simply handle those with an imputation method, added to the random forest: \itemize{ -\item{If a numeric value is inactive, i.e., missing, it will be imputed by 2 times the - maximum of observed values} -\item{If a categorical value is inactive, i.e., missing, it will be imputed by the - special class label \code{"__miss__"}} +\item If a numeric value is inactive, i.e., missing, it will be imputed by 2 times the + maximum of observed values +\item If a categorical value is inactive, i.e., missing, it will be imputed by the + special class label \code{"__miss__"} } Both of these techniques make sense for tree-based methods and are usually hard to beat, see Ding et.al. (2010). diff --git a/man/makeMBOTrafoFunction.Rd b/man/makeMBOTrafoFunction.Rd index bb4dcd511..c8abbdd86 100644 --- a/man/makeMBOTrafoFunction.Rd +++ b/man/makeMBOTrafoFunction.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/makeMBOTrafoFunction.R \name{makeMBOTrafoFunction} \alias{makeMBOTrafoFunction} -\title{Create a transformation function for MBOExampleRun.} +\title{Create a transformation function for MBOExampleRun} \usage{ makeMBOTrafoFunction(name, fun) } diff --git a/man/mbo.Rd b/man/mbo.Rd index 66b59a806..19999be30 100644 --- a/man/mbo.Rd +++ b/man/mbo.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/mbo.R \name{mbo} \alias{mbo} -\title{Optimizes a function with sequential model based optimization.} +\title{Optimizes a function with sequential model based optimization} \usage{ mbo( fun, diff --git a/man/mboContinue.Rd b/man/mboContinue.Rd index dd3d69413..cc514a5e2 100644 --- a/man/mboContinue.Rd +++ b/man/mboContinue.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/mboContinue.R \name{mboContinue} \alias{mboContinue} -\title{Continues an mbo run from a save-file.} +\title{Continues an mbo run from a save-file} \usage{ mboContinue(opt.state) } diff --git a/man/mboFinalize.Rd b/man/mboFinalize.Rd index ab5090933..10bcae034 100644 --- a/man/mboFinalize.Rd +++ b/man/mboFinalize.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/mboFinalize.R \name{mboFinalize} \alias{mboFinalize} -\title{Finalizes an mbo run from a save-file.} +\title{Finalizes an mbo run from a save-file} \usage{ mboFinalize(file) } diff --git a/man/mbo_OptPath.Rd b/man/mbo_OptPath.Rd index 7fd10f869..ea0c8ae4c 100644 --- a/man/mbo_OptPath.Rd +++ b/man/mbo_OptPath.Rd @@ -14,10 +14,10 @@ The extras are: \item{prop.type}{Type of point proposal. Possible values are \describe{ \item{initdesign}{Points actually not proposed, but in the initial design.} - \item{infill\_x}{Here x is a placeholder for the selected infill criterion, e.g., infill\_ei for expected improvement.} - \item{random\_interleave}{Uniformly sampled points added additionally to the proposed points.} - \item{random\_filtered}{If filtering of proposed points located too close to each other is active, these are replaced by random points.} - \item{final\_eval}{If \code{final.evals} is set in \code{\link{makeMBOControl}}: Final evaluations of the proposed solution to reduce noise in y.} + \item{infill_x}{Here x is a placeholder for the selected infill criterion, e.g., infill_ei for expected improvement.} + \item{random_interleave}{Uniformly sampled points added additionally to the proposed points.} + \item{random_filtered}{If filtering of proposed points located too close to each other is active, these are replaced by random points.} + \item{final_eval}{If \code{final.evals} is set in \code{\link{makeMBOControl}}: Final evaluations of the proposed solution to reduce noise in y.} } } \item{parego.weight}{Weight vector sampled for multi-point ParEGO} diff --git a/man/mbo_parallel.Rd b/man/mbo_parallel.Rd index ca383e3ab..d50464940 100644 --- a/man/mbo_parallel.Rd +++ b/man/mbo_parallel.Rd @@ -5,7 +5,7 @@ \title{Parallelization in mlrMBO} \description{ In mlrMBO you can parallelize the tuning on two different levels to speed up computation: -\itemize{ +\describe{ \item{\code{mlrMBO.feval}}{Multiple evaluations of the target function.} \item{\code{mlrMBO.propose.points}}{Optimization of the infill criteria if multiple are used (e.g. ParEGO and ParallelLCB)} } @@ -14,8 +14,8 @@ See the mlrMBO tutorial and the Github project pages of parallelMap for instruct The different levels of parallelization can be specified in \code{parallelStart*}. Details for the levels mentioned above are given below: \itemize{ -\item{Evaluation of the objective function can be parallelized in cases multiple points are to be evaluated at once. These are: evaluation of the initial design, multiple proposed points per iteration and evaluation of the target function in \code{\link{exampleRun}}. (Level: \code{mlrMBO.feval})} -\item{Model fitting / point proposal - in some cases where independent, expensive operations are performed. (Level: \code{mlrMBO.propose.points})} +\item Evaluation of the objective function can be parallelized in cases multiple points are to be evaluated at once. These are: evaluation of the initial design, multiple proposed points per iteration and evaluation of the target function in \code{\link{exampleRun}}. (Level: \code{mlrMBO.feval}) +\item Model fitting / point proposal - in some cases where independent, expensive operations are performed. (Level: \code{mlrMBO.propose.points}) } Details regarding the latter: \describe{ diff --git a/man/plotExampleRun.Rd b/man/plotExampleRun.Rd index e013a8a68..8d5e75b47 100644 --- a/man/plotExampleRun.Rd +++ b/man/plotExampleRun.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/plotExampleRun.R \name{plotExampleRun} \alias{plotExampleRun} -\title{Renders plots for exampleRun objects and displays them.} +\title{Renders plots for exampleRun objects and displays them} \usage{ plotExampleRun( object, diff --git a/man/print.MBOControl.Rd b/man/print.MBOControl.Rd index 9411f91bc..7f38bceeb 100644 --- a/man/print.MBOControl.Rd +++ b/man/print.MBOControl.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/makeMBOControl.R \name{print.MBOControl} \alias{print.MBOControl} -\title{Print mbo control object.} +\title{Print mbo control object} \usage{ \method{print}{MBOControl}(x, ...) } @@ -14,5 +14,5 @@ Control object.} Not used.} } \description{ -Print mbo control object. +Print mbo control object } diff --git a/man/renderExampleRunPlot.Rd b/man/renderExampleRunPlot.Rd index ad7f7113d..38b05382f 100644 --- a/man/renderExampleRunPlot.Rd +++ b/man/renderExampleRunPlot.Rd @@ -3,7 +3,7 @@ \name{renderExampleRunPlot} \alias{renderExampleRunPlot} \title{Renders plots for exampleRun objects, either in 1D or 2D, or -exampleRunMultiObj objects.} +exampleRunMultiObj objects} \usage{ renderExampleRunPlot( object, diff --git a/man/setMBOControlInfill.Rd b/man/setMBOControlInfill.Rd index 31982a348..054aef693 100644 --- a/man/setMBOControlInfill.Rd +++ b/man/setMBOControlInfill.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/setMBOControlInfill.R \name{setMBOControlInfill} \alias{setMBOControlInfill} -\title{Extends mbo control object with infill criteria and infill optimizer options.} +\title{Extends mbo control object with infill criteria and infill optimizer options} \usage{ setMBOControlInfill( control, diff --git a/man/setMBOControlMultiObj.Rd b/man/setMBOControlMultiObj.Rd index 1316b6da2..68ae9c8ff 100644 --- a/man/setMBOControlMultiObj.Rd +++ b/man/setMBOControlMultiObj.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/setMBOControlMultiObj.R \name{setMBOControlMultiObj} \alias{setMBOControlMultiObj} -\title{Set multi-objective options.} +\title{Set multi-objective options} \usage{ setMBOControlMultiObj( control, @@ -93,6 +93,7 @@ Extends MBO control object with multi-objective specific options. \references{ For more information on the implemented multi-objective procedures the following sources might be helpful: + Knowles, J.: ParEGO: A hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems. IEEE Transactions on Evolutionary Computation, 10 (2006) 1, pp. 50-66 @@ -116,8 +117,8 @@ an Event Detection Software under Limited Budgets. In: Proc. 7th International. Conf. Evolutionary Multi-Criterion Optimization (EMO 2013), March 19-22, Sheffield, UK, R. Purshouse; P. J. Fleming; C. M. Fonseca; S. Greco; J. Shaw, eds., 2013, vol. 7811 of Lecture -Notes in Computer Science, ISBN 978-3-642-37139-4, pp. 756{770, -doi:10.1007/978-3-642-37140-0 56} +Notes in Computer Science, ISBN 978-3-642-37139-4, pp. 756-770, +doi:10.1007/978-3-642-37140-0 56 Jeong, S.; Obayashi, S.: Efficient global optimization (EGO) for Multi-Objective Problem and Data Mining. In: Proc. IEEE Congress on diff --git a/man/setMBOControlMultiPoint.Rd b/man/setMBOControlMultiPoint.Rd index 11eabb2f7..22a5e0457 100644 --- a/man/setMBOControlMultiPoint.Rd +++ b/man/setMBOControlMultiPoint.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/setMBOControlMultiPoint.R \name{setMBOControlMultiPoint} \alias{setMBOControlMultiPoint} -\title{Set multipoint proposal options.} +\title{Set multipoint proposal options} \usage{ setMBOControlMultiPoint( control, diff --git a/man/setMBOControlTermination.Rd b/man/setMBOControlTermination.Rd index 48517a226..7e15a8d30 100644 --- a/man/setMBOControlTermination.Rd +++ b/man/setMBOControlTermination.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/setMBOControlTermination.R \name{setMBOControlTermination} \alias{setMBOControlTermination} -\title{Set termination options.} +\title{Set termination options} \usage{ setMBOControlTermination( control, diff --git a/man/trafos.Rd b/man/trafos.Rd index 0d6374cf9..5c1d42915 100644 --- a/man/trafos.Rd +++ b/man/trafos.Rd @@ -4,7 +4,7 @@ \alias{trafos} \alias{trafoLog} \alias{trafoSqrt} -\title{Transformation methods.} +\title{Transformation methods} \format{ None } @@ -24,9 +24,9 @@ What should be done, if negative values occur? Setting this option to stops the process immediately.} } \description{ -\itemize{ - \item{\bold{logTrafo}}{\cr Natural logarithm.} - \item{\bold{sqrtTrafo}}{\cr Square root.} +\describe{ + \item{\bold{logTrafo}}{Natural logarithm.} + \item{\bold{sqrtTrafo}}{Square root.} } If negative values occur and the trafo function can handle only positive values, a shift of the form x - min(x) + 1 is performed prior to the transformation if the