Authors@R: c(person("Quang", "Huynh", email = "quang@bluematterscience.com", role = c("aut", "cre")),
person("Todd", "Gedamke", role = "ctb"),

Title: Machine Learning Model Evaluation
Maintainer: Christopher R John <chris.r.john86@gmail.com>
Description: Straightforward and detailed evaluation of machine learning models. 'MLeval' can produce receiver operating characteristic curves (ROCs), precision-recall (PR) curves, and PR gain curves. 'MLeval' can automatically interpret the Caret train function results from repeated cross validation, select the best model, and produces a number of evaluation metrics with confidence intervals.
Packaged: 2019-11-21 06:56:57 UTC; christopher

Description: Straightforward and detailed evaluation of machine learning models. 'MLeval' can produce receiver operating characteristic (ROC) curves, precision-recall (PR) curves, calibration curves, and PR gain curves. 'MLeval' accepts a data frame of class probabilities and ground truth labels, or, it can automatically interpret the Caret train function results from repeated cross validation, then select the best model and analyse the results. 'MLeval' produces a range of evaluation metrics with confidence intervals.
Packaged: 2019-11-28 06:58:55 UTC; christopher

Packaged: 2020-02-11 10:01:27 UTC; christopher

Title: Machine Learning Evaluation Metrics
Description: A collection of evaluation metrics, including loss, score and utility functions,
that measure regression and classification performance.
Packaged: 2015-05-02 03:36:34 UTC; Administrator

Description: A collection of evaluation metrics, including loss, score and
utility functions, that measure regression, classification and ranking performance.
Packaged: 2016-05-01 11:07:14 UTC; Administrator

Packaged: 2016-05-09 06:13:55 UTC; Administrator

Title: Maximum Likelihood Estimation of the Niche Preemption Model
Authors@R: person("Jan", "Graffelman", role = c("aut", "cre"), email = "jan.graffelman@upc.edu")
Description: Provides functions for obtaining estimates of the parameter of the niche preemption model (also known as the geometric series), in particular a maximum likelihood estimator (Graffelman, 2021) <doi:10.1101/2021.01.27.428381>. The niche preemption model is a widely used model in ecology and biodiversity studies.