Package: sillysplines 1.0.1
sillysplines: Linear Splines to Generate Decision Boundaries
Create two dimensional datasets with decision boundaries set by linear splines. An HTML widget enables users to draw the splines on a web page and generate a JSON file that can be used to generate datasets.
Authors:
sillysplines_1.0.1.tar.gz
sillysplines_1.0.1.zip(r-4.7-any)sillysplines_1.0.1.zip(r-4.6-any)sillysplines_1.0.1.zip(r-4.5-any)
sillysplines_1.0.1.tgz(r-4.6-any)sillysplines_1.0.1.tgz(r-4.5-any)
sillysplines_1.0.1.tar.gz(r-4.7-any)sillysplines_1.0.1.tar.gz(r-4.6-any)
sillysplines_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
sillysplines/json (API)
| # Install 'sillysplines' in R: |
| install.packages('sillysplines', repos = c('https://janithwanni.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/janithwanni/sillysplines/issues
Pkgdown/docs site:https://janithwanni.github.io
Last updated from:3fd957b40f. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 126 | ||
| source / vignettes | OK | 247 | ||
| linux-release | OK | 130 | ||
| macos-release | OK | 90 | ||
| macos-oldrel | OK | 85 | ||
| windows-devel | OK | 72 | ||
| windows-release | OK | 62 | ||
| windows-oldrel | OK | 66 | ||
| wasm-release | OK | 124 |
Exports:add_noise_varsclassify_boundarycreate_datarenderSillysplinessillysplinessillysplinesOutputtrim_shape
Dependencies:base64encbslibcachemclidigestevaluatefastmapfontawesomefshighrhtmltoolshtmlwidgetsjquerylibjsonliteknitrlifecyclememoisemimeR6rappdirsrlangrmarkdownsasstinytexwithrxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Add noise variables to create high-dimensional data | add_noise_vars |
| Classify Points Relative to a Boundary Line | classify_boundary |
| Create a 2D Synthetic Dataset With Class Labels | create_data |
| Create a box to draw silly spline | sillysplines |
| Shiny bindings for sillysplines | renderSillysplines sillysplinesOutput |
| Trim data to be have correlated predictors | trim_shape |