Package: maize 0.0.2.95

maize: Specialty Kernels for SVMs

Bindings for SVMs and special kernels via kernlab, e1701, ebmc, and mildsvm extending the 'parsnip' package. Specifically related to kernels for support vector machines not available in parsnip. Package also includes interfaces for novel SVM preprocessors (recipes) and postprocessors (probably).

Authors:Frank Hull [aut, cre], Max Kuhn [ctb]

maize_0.0.2.95.tar.gz
maize_0.0.2.95.zip(r-4.7-any)maize_0.0.2.95.zip(r-4.6-any)maize_0.0.2.95.zip(r-4.5-any)
maize_0.0.2.95.tgz(r-4.6-any)maize_0.0.2.95.tgz(r-4.5-any)
maize_0.0.2.95.tar.gz(r-4.7-any)maize_0.0.2.95.tar.gz(r-4.6-any)
maize_0.0.2.95.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
maize/json (API)

# Install 'maize' in R:
install.packages('maize', repos = c('https://frankiethull.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/frankiethull/maize/issues

Pkgdown/docs site:https://frankiethull.github.io

Datasets:
  • corn_data - Synthetic Corn Dataset for Corny Example

On CRAN:

Conda:

quarto

4.86 score 12 stars 15 scripts 53 exports 108 dependencies

Last updated from:e50678f6b4. Checks:7 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develWARNING270
source / vignettesOK879
linux-releaseWARNING257
macos-releaseWARNING252
macos-oldrelWARNING275
windows-develWARNING192
windows-releaseWARNING231
windows-oldrelWARNING224
wasm-releaseOK178

Exports:ada_boost_svm_rbfalphaapd_svm_novel_detectionarima_svm_laplacearima_svm_laplace_fit_implarima_svm_predict_implauto_arima_svm_laplace_fit_implbag_svm_rbfbessel_ordercal_apply_regressioncal_estimate_svmcheck_argsimb_ratioint_conformal_quantile_svmkcca_correlatekqr_laplaceksvm_stringdotlssvm_laplacemisvm_orova_fit_specmisvm_orova_rbfmisvm_predict_specnum_learnerspredict_ksvm_stringdot_classpredict_ksvm_stringdot_probrus_boost_svm_rbfrvm_laplacestep_kfa_laplacestep_kfm_nystromstep_kha_laplacestep_kha_tanhstep_kpca_laplacestep_kpca_tanhstring_lambdastring_lengthstring_normalizedsvm_anova_rbfsvm_besselsvm_cauchysvm_cossimsvm_fouriersvm_laplacesvm_sorensensvm_splinesvm_stringsvm_tanhsvm_tanimotosvm_tstudentsvm_wavelettauvarwavelet_awavelet_cwavelet_h

Dependencies:applicablebase64encbslibbutchercachemclasscliclockcodetoolscpp11crayondata.tablediagramdialsDiceDesigndigestdplyrevaluatefarverfastmapfontawesomefsfurrrfuturefuture.applyGauProgenericsggplot2globalsgluegowergtablehardhathighrhtmltoolsipredisobandjquerylibjsonliteKernSmoothknitrlabelinglatticelavalbfgslifecyclelistenvlobstrlubridatemagrittrMASSMatrixmemoisemimemixoptmodelenvnnetnumDerivparallellyparsnippillarpkgconfigprettyunitsprobablyprodlimprogressrproxyCpurrrR6rappdirsRColorBrewerRcppRcppArmadillorecipesrlangrmarkdownrpartrsampleS7sassscalessfdshapeslidersparsevctrssplitfngrSQUAREMstringistringrsurvivaltailortibbletidyrtidyselecttimechangetimeDatetinytextunetzdbutf8vctrsviridisLitewarpwithrworkflowsxfunyamlyardstick

glass-gem
{maize} for novelty detection | isolation forest score method | SVM novelty detection score method | {maize} for kernel canonical correlation analysis | kernel canonical correlation analysis
Rendered fromglass-gem.qmdusingquarto::html

Last update: 2026-10-14
Started: 2025-05-31

two-class-post-processing
two types of corn kernels we need to classify: | create a three-way split using rsample: | train a classification svm using workflows: | detecting class with {maize} and [EQ] thresholding via probably | calibration with probably
Rendered fromtwo-class-post-processing.qmdusingquarto::html

Last update: 2026-10-14
Started: 2024-12-03

perchance
Post-Processing in {maize}??? | Key Components | Implementation Details | Dependency Note | point and interval regressions | predict with intervals | check conformal quantile prediction intervals | SVM with QRF & QRSVM Prediction Intervals | SVM with Linear & SVM Calibration
Rendered fromperchance.Rmdusingknitr::rmarkdown

Last update: 2025-06-01
Started: 2025-03-14

harvestime
{maize} for time series | ARIMA + SVM Errors | Calibrated AutoARIMA vs. AutoARIMA w/ 'SVM Laplacian Kernel' Errors predictions: | Recursive SVMs
Rendered fromharvestime.qmdusingquarto::html

Last update: 2025-04-26
Started: 2025-04-26

pre-processors-in-maize
kernel recipes | Corn Dataset | Kernel PCA | Laplace PCA | Kernel Hebbian Algorithm | Laplace Hebbian | Kernel Feature Analysis | Laplace Feature Analysis | Nystrom Kernel Feature Map
Rendered frompre-processors-in-maize.qmdusingquarto::html

Last update: 2025-04-12
Started: 2025-04-12

SVMs
Example Overview | corn kernels and svm kernels | corn kernel dataset | Regression | regression for corn kernel height given a specialty svm kernel | Classification | classification of corn kernel type given a specialty svm kernel
Rendered fromSVMs.Rmdusingknitr::rmarkdown

Last update: 2025-04-02
Started: 2025-04-02

ensembling weak learners in maize
Boosting & Bagging with | Random Under Sampling (RUS) Bagging with SVMs | Random Under Sampling with Boosting, RUSBoost with SVMs | Adaptive Boosting, AdaBoost with SVMs
Rendered fromensembling_weak_learners.Rmdusingknitr::rmarkdown

Last update: 2025-04-02
Started: 2025-04-02

new engines in maize
kernels for the ksvm engine | SVM | beyond the ksvm engine | KQR | LSSVM | RVM
Rendered fromextending_kernlab_support.Rmdusingknitr::rmarkdown

Last update: 2025-04-02
Started: 2025-04-02

Readme and manuals

Help Manual

Help pageTopics
AdaBoost SVM with Radial Basis Function Kernelada_boost_svm_rbf
Fit an SVM novelty detection model to estimate an applicability domain.apd_svm_novel_detection apd_svm_novel_detection.data.frame apd_svm_novel_detection.default apd_svm_novel_detection.formula apd_svm_novel_detection.matrix apd_svm_novel_detection.recipe
General Interface for "Support Vector Machine" ARIMA Regression Modelsarima_svm_laplace
visualize component x-y feature spaceautoplot.kcor_df
RUS Bagged SVM with Radial Basis Function Kernelbag_svm_rbf
Uses a support vector regression model to calibrate numeric predictionscal_estimate_svm cal_estimate_svm.data.frame cal_estimate_svm.grouped_df cal_estimate_svm.tune_results
Synthetic Corn Dataset for Corny Examplecorn_data
Prediction intervals via conformal inference and QRSVMint_conformal_quantile_svm int_conformal_quantile_svm.workflow
Kernel Canonical Correlation Analysiskcca_correlate
Laplacian Kernel Quantile Regressionkqr_laplace
Laplacian Least Squares Support Vector Machinelssvm_laplace
Multiple Instance SVMs for Ordinal Outcome Data, One-Vs-All, with Radial Basis Function Kernelmisvm_orova_rbf
RUSBoost SVM with Radial Basis Function Kernelrus_boost_svm_rbf
Laplacian Relevance Vector Machine (Experimental RVM)rvm_laplace
Predict from a 'apd_svm_novel_detection'score.apd_svm_novel_detection
Laplacian function kernel KFA signal extractionstep_kfa_laplace
Nystrom kernel feature map approximation (RBF)step_kfm_nystrom
Laplacian function kernel PCA signal extraction via Hebbian Algorithmstep_kha_laplace
tanh function kernel PCA signal extraction via Hebbian Algorithmstep_kha_tanh
Laplacian function kernel PCA signal extractionstep_kpca_laplace
Laplacian function kernel PCA signal extractionstep_kpca_tanh
ANOVA RBF Support Vector Machinesvm_anova_rbf
Bessel Support Vector Machinesvm_bessel
Cauchy Support Vector Machinesvm_cauchy
Cosine Similarity Support Vector Machinesvm_cossim
Fourier Support Vector Machinesvm_fourier
Laplacian Support Vector Machinesvm_laplace
Sorensen Support Vector Machinesvm_sorensen
Spline Support Vector Machinesvm_spline
String Support Vector Machinesvm_string
Hyperbolic Tangent Support Vector Machinesvm_tanh
Tanimoto Support Vector Machinesvm_tanimoto
T-Student Support Vector Machinesvm_tstudent
Wavelet Support Vector Machinesvm_wavelet