Package: BinarybalancedCut 0.2
BinarybalancedCut: Threshold Cut Point of Probability for a Binary Classifier Model
Allows to view the optimal probability cut-off point at which the Sensitivity and Specificity meets and its a best way to minimize both Type-1 and Type-2 error for a binary Classifier in determining the Probability threshold.
Authors:
BinarybalancedCut_0.2.tar.gz
BinarybalancedCut_0.2.zip(r-4.5)BinarybalancedCut_0.2.zip(r-4.4)BinarybalancedCut_0.2.zip(r-4.3)
BinarybalancedCut_0.2.tgz(r-4.4-any)BinarybalancedCut_0.2.tgz(r-4.3-any)
BinarybalancedCut_0.2.tar.gz(r-4.5-noble)BinarybalancedCut_0.2.tar.gz(r-4.4-noble)
BinarybalancedCut_0.2.tgz(r-4.4-emscripten)BinarybalancedCut_0.2.tgz(r-4.3-emscripten)
BinarybalancedCut.pdf |BinarybalancedCut.html✨
BinarybalancedCut/json (API)
| # Install 'BinarybalancedCut' in R: |
| install.packages('BinarybalancedCut', repos = c('https://navinkumarnedunchezhian.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 7 years agofrom:9d8811dcb2. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 16 2024 |
| R-4.5-win | OK | Nov 16 2024 |
| R-4.5-linux | OK | Nov 16 2024 |
| R-4.4-win | OK | Nov 16 2024 |
| R-4.4-mac | OK | Nov 16 2024 |
| R-4.3-win | OK | Nov 16 2024 |
| R-4.3-mac | OK | Nov 16 2024 |
Exports:Binary_threshold
Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrR6RColorBrewerRcppreshape2rlangscalesstringistringrtibbleutf8vctrsviridisLitewithr
