Package: scR 0.3.0

Perry Carter

scR: Estimate Vapnik-Chervonenkis Dimension and Sample Complexity

We provide a suite of tools for estimating the sample complexity of a chosen model through theoretical bounds and simulation. The package incorporates methods for estimating the Vapnik-Chervonenkis dimension (VCD) of a chosen algorithm, which can be used to estimate its sample complexity. Alternatively, we provide simulation methods to estimate sample complexity directly. For more details, see Carter, P & Choi, D (2024). "Learning from Noise: Applying Sample Complexity for Political Science Research" <doi:10.31219/osf.io/evrcj>.

Authors:Perry Carter [aut, cre], Dahyun Choi [aut]

scR_0.3.0.tar.gz
scR_0.3.0.tar.gz(r-4.5-noble)scR_0.3.0.tar.gz(r-4.4-noble)
scR_0.3.0.tgz(r-4.4-emscripten)scR_0.3.0.tgz(r-4.3-emscripten)
scR.pdf |scR.html✨
scR/json (API)

# Install 'scR' in R:

install.packages('scR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/pjesscarter/scr/issues

Datasets:

br - Replication data for 'Predicting Recidivism'

2.00 score 4 scripts 183 downloads 7 exports 107 dependencies

Last updated 7 days agofrom:3fcc0a3eee. Checks:OK: 2. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Dec 18 2024
R-4.5-linux	OK	Dec 18 2024

Exports:acc_sim estimate_accuracy gendata getpac plot_accuracy scb simvcd

Dependencies:askpass base64enc bslib cachem caret class cli clock codetools colorspace cpp11 crosstalk curl data.table diagram digest dplyr e1071 evaluate fansi farver fastmap fontawesome foreach fs future future.apply generics ggplot2 globals glue gower gtable hardhat highr htmltools htmlwidgets httr ipred isoband iterators jquerylib jsonlite KernSmooth knitr labeling later lattice lava lazyeval lifecycle listenv lubridate magrittr MASS Matrix memoise mgcv mime ModelMetrics munsell nlme nnet numDeriv openssl parallelly pbapply pillar pkgconfig plotly plyr pROC prodlim progressr promises proxy purrr R6 rappdirs RColorBrewer Rcpp recipes reshape2 rlang rmarkdown rpart sass scales shape SQUAREM stringi stringr survival sys tibble tidyr tidyselect timechange timeDate tinytex tzdb utf8 vctrs viridisLite withr xfun yaml

Help page	Topics
Utility function to generate accuracy metrics, for use with 'estimate_accuracy()'	acc_sim
Replication data for 'Predicting Recidivism'	br
Estimate sample complexity bounds for a binary classification algorithm using either simulated or user-supplied data.	estimate_accuracy
Simulate data with appropriate structure to be used in estimating sample complexity bounds	gendata
Recalculate achieved sample complexity bounds given different parameter inputs	getpac
Utility function to define the least-squares loss function to be optimized for 'simvcd()'	loss
Represent simulated sample complexity bounds graphically	plot_accuracy
Utility function to generate data points for estimation of the VC Dimension of a user-specified binary classification algorithm given a specified sample size.	risk_bounds
Calculate sample complexity bounds for a classifier given target accuracy	scb
Estimate the Vapnik-Chervonenkis (VC) dimension of an arbitrary binary classification algorithm.	simvcd

Package: scR 0.3.0

scR: Estimate Vapnik-Chervonenkis Dimension and Sample Complexity

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