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)srsbench_0.1.zip(r-4.6)srsbench_0.1.zip(r-4.5)
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:

1.70 score 1 stars 4 exports 0 dependencies

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

Target	Result	Time
linux-devel-x86_64	OK	101
source / vignettes	OK	181
linux-release-x86_64	OK	99
macos-release-arm64	OK	81
macos-oldrel-arm64	OK	67
windows-devel	OK	97
windows-release	OK	60
windows-oldrel	OK	69
wasm-release	OK	83

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