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cutpointr  

Determine and Evaluate Optimal Cutpoints in Binary Classification Tasks
View on CRAN: Click here


Download and install cutpointr package within the R console
Install from CRAN:
install.packages("cutpointr")

Install from Github:
library("remotes")
install_github("cran/cutpointr")

Install by package version:
library("remotes")
install_version("cutpointr", "1.1.2")



Attach the package and use:
library("cutpointr")
Maintained by
Christian Thiele
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-03-21
Latest Update: 2022-04-13
Description:
Estimate cutpoints that optimize a specified metric in binary classification tasks and validate performance using bootstrapping. Some methods for more robust cutpoint estimation are supported, e.g. a parametric method assuming normal distributions, bootstrapped cutpoints, and smoothing of the metric values per cutpoint using Generalized Additive Models. Various plotting functions are included. For an overview of the package see Thiele and Hirschfeld (2021) .
How to cite:
Christian Thiele (2018). cutpointr: Determine and Evaluate Optimal Cutpoints in Binary Classification Tasks. R package version 1.1.2, https://cran.r-project.org/web/packages/cutpointr
Previous versions and publish date:
0.7.2 (2018-03-21 10:27), 0.7.3 (2018-04-13 15:16), 0.7.4 (2018-08-31 18:50), 0.7.6 (2019-03-27 11:10), 1.0.0 (2019-09-17 23:30), 1.0.1 (2019-12-18 16:00), 1.0.2 (2020-04-14 10:50), 1.0.32 (2020-06-19 14:00), 1.1.0 (2021-02-15 15:40), 1.1.1 (2021-06-29 08:30)
Other packages that cited cutpointr R package
View cutpointr citation profile
Other R packages that cutpointr depends, imports, suggests or enhances
Functions, R codes and Examples using the cutpointr R package
Some associated functions: F1_score . Jaccard . abs_d_ppv_npv . abs_d_sens_spec . accuracy . add_metric . auc . boot_ci . boot_test . cohens_kappa . cutpoint . cutpoint_knots . cutpointr . cutpointr_ . false_omission_rate . maximize_boot_metric . maximize_gam_metric . maximize_loess_metric . maximize_metric . maximize_spline_metric . metric_constrain . misclassification_cost . multi_cutpointr . npv . oc_manual . oc_mean . oc_median . oc_youden_kernel . oc_youden_normal . odds_ratio . p_chisquared . plot.cutpointr . plot.multi_cutpointr . plot.roc_cutpointr . plot_cut_boot . plot_cutpointr . plot_metric . plot_metric_boot . plot_precision_recall . plot_roc . plot_sensitivity_specificity . plot_x . plr . ppv . precision . predict.cutpointr . print.cutpointr . print.multi_cutpointr . prod_ppv_npv . prod_sens_spec . prostate_nodal . recall . risk_ratio . roc . roc01 . sensitivity . specificity . suicide . sum_ppv_npv . sum_sens_spec . total_utility . tp . tpr . user_span_cutpointr . youden . 
Some associated R codes: RcppExports.R . add_metric.R . boot_ci.R . boot_test.R . compat-lifecycle.R . cutpointr.R . data.R . globals.R . grid_arrange_shared_legend.R . metrics.R . oc_manual.R . oc_mean.R . oc_median.R . oc_youden_kernel.R . oc_youden_normal.R . optimize_metric.R . plot.cutpointr.R . plot.multi_cutpointr.R . plot_cut_boot.R . plot_cutpointr.R . plot_metric.R . plot_metric_boot.R . plot_precision_recall.R . plot_roc.R . plot_sensitivity_specificity.R . plot_x.R . predict.cutpointr.R . prep.R . print.cutpointr.R . print.multi_cutpointr.R . print.summary_cutpointr.R . print.summary_multi_cutpointr.R . roc.R . summary.cutpointr.R . summary.multi_cutpointr.R . utils.R .  Full cutpointr package functions and examples
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