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SPOT (version 2.9.52)

Sequential Parameter Optimization Toolbox

Description

A set of tools for model-based optimization and tuning of algorithms (hyperparameter tuning respectively hyperparameter optimization). It includes surrogate models, optimizers, and design of experiment approaches. The main interface is spot, which uses sequentially updated surrogate models for the purpose of efficient optimization. The main goal is to ease the burden of objective function evaluations, when a single evaluation requires a significant amount of resources.

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Version

Install

install.packages('SPOT')

Monthly Downloads

201

Version

2.9.52

License

GPL (>= 2)

Maintainer

Thomas Bartz-Beielstein

Last Published

May 1st, 2022

Functions in SPOT (2.9.52)

Build LOESS Model

buildKrigingDACE

Build DACE model

buildGaussianProcess

Gaussian Process Model Interface

Bayesian Optimization Model Interface

Build Kriging Model

Linear Model Interface

buildEnsembleStack

Ensemble: Stacking

Build random search dummy model

checkInputTypesInControl

Check input types in the spotControl list.

Latin Hypercube Design Generator

calculationBarthMuschelknautz

Cyclone Simulation: Barth/Muschelknautz

buildRandomForest

Random Forest Interface

Build Response Surface Model

Lasso Model Interface

Normalized LHD Design

checkFunEvalsDesignSize

Check funEvals Setting against designSize

checkVerbosityLevels

Check correct verbosity levels

checkTypesOfInput

Check Input Types

checkInputDimensionsionalityCorrect

Check Dimensions of spotInputs

Sequential Parameter Optimization Toolbox

ranger Interface

Correlation: Spline

Prepare DACE fit

checkLowerSmallerThanUpper

#' Check That Lower and Upper are not Equal #' #' If any entries in lower and upper are equal, the parameter has no range and cant be optimized. #' In that case, an error is generated. #' #' @param lower is a vector that defines the lower boundary of search space. This determines also the dimensionality of the problem. #' @param upper is a vector that defines the upper boundary of search space. #' #' @keywords internal checkLowerNotEqualsUpper <- function(lower,upper) if(any(lower == upper)) stop("SPOT Configuration Error: Entries in 'lower' and 'upper' should not be equal") Check That Lower is smaller than Upper

Correlation: Noisy Gauss

Evaluate Model This function produces an objective function with y=f(x) from a provided model fit. Important note: this function expects predict(object,newdata) to return a list. The object$target parameter is a string that determines which list item is returned by the created function. If not set (NULL), object$target is set to "y".

daceStartParameters

Start parameter setup DACE

Correlation: Lin

expectedImprovement

Expected Improvement

Correlation: Exp

Evaluate DACE fit

Fix model parameters DACE

Gas Sensor Data

Correlation: Expg

Descent RSM model

Transform coded values to natural values

calculationMothes

Cyclone Simulation: Mothes

Correlation: Cubic

Correlation: Gauss

designUniformRandom

Uniform Design Generator

checkFeasibilityNlopGnIngres

Check feasibility for NLOPT_GN_ISRES

Check for NAs in x lower and upper

funPowellS (No. 19, More No. 13)

funBeale (No.11, More No. 5)

Objective function - Cyclone Simulation: Barth/Muschelknautz

funbox3D (No. 18, More No. 12)

funGulf (No.17, More No. 11)

funHelical (No. 13, More No. 7)

funMeyer (No. 16, More No. 10)

Correlation: Kriging

funBranin (No. 1)

funRosen (No. 2, More No. 1)

Parallel execution of code, dependent on the operating system

Correlation: Spherical

duplicateAndReplicateHandling

duplicateAndReplicateHandling

corrnoisykriging

Correlation: Noisy Kriging

funbrownBs (No. 10, More No. 4)

Wrapper for Maximum Likelihood Estimation

getNatDesignFromCoded

Get natural parameter values from coded +-1 representation

getPerformanceStats

get performance stats

optimNLOPTR. Minimization by NLOPT

Wrapper for Expected improvement (Gramacy)

get number of replicates

objectiveFunctionEvaluation

objectiveFunctionEvaluation Objective Function Evaluation

funFreudRoth (No. 8, More No. 2)

getMultiStartPoints

Get Multi Start Points

funOptimLecture

funOptimLecture

infillGetFullPrediction

infillGetFullPrediction

funJennSamp (No. 12, More No 6)

Ishigami Test Function (No. 7)

getCorrelationMatrix

getCorrelationMatrix

Surface plot of a model

Random search surrogate-optimizer

normalizeMatrix

Normalize design

funPowellBs (No. 9, More No. 3)

Sobol and Levitan Test Function (No. 6)

funSphere (No. 3)

normalizeMatrix2

Normalize design 2

predict.cvModel

predict.cvModel

Expected Improvement Infill Criterion

DACE objective function

Minimization by Latin Hypercube Sampling

Interface to minimization based on Gramacy's lagp package

handleNAsKrigingWorst

handleNAsKrigingWorst

print.spotLOESS

Print method for loess model

plotPCAvariance

plotPCAvariance

funBaBSimHospital

Optimization of the BaBSim.Hospital Simulator

Impute NAs and Inf in y

funBard (No. 14, More No. 8)

plotSingleDimFunction

plotSingleDimFunction

Print method for RSM model

print.spotGaussianProcessModel

Print method for Gaussian Process Model

funGauss (No. 15, More No. 9)

initialInputCheck

initialInputCheck. Initial Input Check of Spot Configuration

krigingLikelihood

Calculate negative log-likelihood

print.spotRandomForest

Print method for random forest

funRosen2 (No. 2a)

funGoldsteinPrice

Goldstein-Price Test Function (No. 5)

Minimization by Differential Evolution

plot.spotTreeModel

Plot rpart tree model

Evolution Strategy

Plot Best Objective Value

infillExpectedImprovement

infillExpectedImprovement

Minimization by GENetic Optimization Using Derivatives

predict.spotGaussianProcessModel

Prediction method for Gaussian Process Model

Minimization by L-BFGS-B

funShiftedSphere

funShiftedSphere (No. 4)

predictKrigingReinterpolation

Predict Kriging Model (Re-interpolating)

get impute positions

prepareBestObjectiveVal

Preprocess y Values to Plot Best Objective Value

predict.ensembleStack

Predict Stacked Ensemble

simulate.kriging

Kriging Simulation

Regression: Regpoly1

predict.spotLOESS

Predict loess model

Evolution Strategy Implementation

makeSpotFunList

makeSpotFunList

Termination hps

S-Ring Simulation Data Obtained With SPOT

Regression: Regpoly2

S-Ring Simulation Data Obtained With SPOT

spotAlgEsIndividualInitial

Individual Initialization

maxNearestNeighbourDistance

maxNearestNeighbourDistance

result from the vignette benchmark

spotAlgEsGetSuccessRate

get Success Rate

spotAlgEsDominantReco

spotAlgEsDominantReco

linearAdaptedSE

linearAdaptedSE

print.spotLassoModel

Print method for lasso model

print.spotBOModel

Print method for BO model

Print Function DACE Kriging

predict.kriging

Predict Kriging Model

makeMoreFunList

makeMoreFunList

simulateFunction

simulateFunction

spotAlgEsSelection

spotAlgEsSelection

spotAlgEsStratMutation

spotAlgEsStratMutation

Interpolated plot

Expected improvement (Gramacy)

plot.spotSeverity

Plot method for spotSeverity

print.spotLinearModel

Print method for linear model

predict.spotLassoModel

Prediction method for lasso model

spotAlgEsTermination

repairNonNumeric

Repair Non-numeric Values

predict.spotRanger

Predictor for spotExtraTrees

predict.spotTreeModel

Prediction method for rpart tree models

spotFillControlList

spotFillControlList

predict.spotLinearModel

Prediction method for linear model

print.spotTreeModel

Print method for rpart tree models

spotAlgEsInterRecoBeSw02

spotAlgEsInterRecoBeSw02

Regression: Regpoly0

Surface plot of a function

Optimal Computing Budget Allocation

predict.spotBOModel

Prediction method for bayesian optimization model

predict.spotRSM

Predict RSM model

predict.spotRandomForest

Prediction method for random forest

predict.rsdummy

Predict random search dummy

spotAlgEsMarriage

S-Ring Simulation Data

spotAlgEsInitParentPop

Initialize Parent Population

spotPlotSeverityBasic

spotPlotSeverityBasic

spotSeverityBasic

spotSeverityBasic

spotAlgEsInterReco

spotAlgEsInterReco

wrapSystemCommand

wrapSystemCommand

wrapSystem_parseMatrixToString

wrapSystem_parseMatrixToString

wrapFunctionParallel

Parallelized Function Evaluation Wrapper

selectN. Select n Design Points

Function Evaluation Wrapper

print.spotRanger

Print method for random forest

S-Ring Simulation Data

Interface SANN to SPOT

Satterthwaite Function

print.spotSeverity

Print method for spotSeverity

simulationSpectral

simulationSpectral

simulationDecompose

Kriging Simulation: Decomposition

S-Ring Simulation Data

spotAlgEsMarriageWithReplace

Marriage with replace

thetaNuggetGradient

thetaNuggetGradient

Sequential Parameter Optimization Main Loop

Transform input

spotAlgEsObjMutation

spotAlgEsObjMutation

Backslash operator.

updateSeedFromXnew