Package: srsbench 0.1

srsbench: Evaluation Metrics for Spaced Repetition Schedulers

Calibration and discrimination metrics for spaced-repetition memory models. Provides the sample-weighted binned root mean squared error (RMSE(bins)) used to rank schedulers in the open spaced repetition benchmark, together with log loss, the area under the ROC curve, and calibration curves.

Authors:Christos Longros [aut, cre]

srsbench_0.1.tar.gz
srsbench_0.1.zip(r-4.7-any)srsbench_0.1.zip(r-4.6-any)srsbench_0.1.zip(r-4.5-any)
srsbench_0.1.tgz(r-4.6-any)srsbench_0.1.tgz(r-4.5-any)
srsbench_0.1.tar.gz(r-4.7-any)srsbench_0.1.tar.gz(r-4.6-any)
srsbench_0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
srsbench/json (API)

# Install 'srsbench' in R:

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

Bug tracker:https://github.com/chrislongros/srsbench/issues

On CRAN:

2.70 score 1 stars 230 downloads 4 exports 0 dependencies

Last updated from:087d2524fd. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	88
source / vignettes	OK	154
linux-release	OK	87
macos-release	OK	108
macos-oldrel	OK	88
windows-devel	OK	64
windows-release	OK	53
windows-oldrel	OK	58
wasm-release	OK	78

Exports:calibration_bins log_loss rmse_bins srs_auc

Dependencies:

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Calibration curve in equal-width bins	calibration_bins
Log loss (binary cross-entropy)	log_loss
RMSE in bins for a spaced repetition scheduler	rmse_bins
Area under the ROC curve	srs_auc