Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Summary: Precision-recall (PR) and receiver operating characteristic (ROC) curves are valuable measures of classifier performance. Here,  present the R-package PRROC, which allows for computing and visualizing both PR and ROC curves. In contrast to available R-packages, PRROC allows for computing PR and ROC curves and areas under these curves for soft-labeled data using a continuous interpolation beten the points of PR curves. In addition, PRROC provides a generic plot function for generating publication-quality graphics of PR and ROC curves.#R##N##R##N#Availability and implementation: PRROC is available from CRAN and is licensed under GPL 3.#R##N##R##N#Contact: ed.ellah-inu.kitamrofni@uarg
['Jan Grau', 'Ivo Grosse', 'Jens Keilwagen']
I am writing a research paper on a idea PRROC: computing and visualizing precision-recall and receiver operating characteristic curves in R
[{"from": "human", "value": "I am writing a research paper on a idea PRROC: computing and visualizing precision-recall and receiver operating characteristic curves in R"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Summary: Precision-recall (PR) and receiver operating characteristic (ROC) curves are valuable measures of classifier performance. Here,  present the R-package PRROC, which allows for computing and visualizing both PR and ROC curves. In contrast to available R-packages, PRROC allows for computing PR and ROC curves and areas under these curves for soft-labeled data using a continuous interpolation beten the points of PR curves. In addition, PRROC provides a generic plot function for generating publication-quality graphics of PR and ROC curves.#R##N##R##N#Availability and implementation: PRROC is available from CRAN and is licensed under GPL 3.#R##N##R##N#Contact: ed.ellah-inu.kitamrofni@uarg"}]