Description: Arithmetic operations scalar multiplication, addition, subtraction, multiplication and division of LR fuzzy numbers (which are on the basis of extension principle) have a complicate form for using in fuzzy Statistics, fuzzy Mathematics, machine learning, fuzzy data analysis and etc. Calculator for LR Fuzzy Numbers package relieve and aid applied users to achieve a simple and closed form for some complicated operator based on LR fuzzy numbers and also the user can easily draw the membership function of the obtained result by this package.

Title: Code Calibration in a Bayesian Framework
Authors@R: c(person("Mathieu", "Carmassi", email = "mathieu.carmassi@gmail.com",role = c("aut", "cre")))
Description: Calibration of every computational code. It uses a Bayesian framework to rule the estimation. With a new data set, the prediction will create a prevision set taking into account the new calibrated parameters. The choices between several models is also available. The methods are described in the paper Carmassi et al. (2018) <arXiv:1801.01810>.
Imports: R6, ggplot2, FactoMineR, DiceKriging, DiceDesign, MASS, coda,
Collate: 'functions.R' 'models.R' 'prediction.R' 'prior.R'
Packaged: 2018-03-14 21:23:23 UTC; mathieucarmassi

Imports: R6, ggplot2, DiceKriging, DiceDesign, MASS, coda, parallel,
Collate: 'functions.R' 'models.R' 'forecast.R' 'prior.R'

Title: Mapping ML Scores to Calibrated Predictions
Description: Transforms your uncalibrated Machine Learning scores to well-calibrated prediction estimates that can be interpreted as probability estimates. The implemented BBQ (Bayes Binning in Quantiles) model is taken from Naeini (2015, ISBN:0-262-51129-0).
Imports: ggplot2, pROC, reshape2, parallel, foreach, utils, stats,

Imports: ggplot2, pROC, reshape2, parallel, foreach, stats,

Description: Transforms your uncalibrated Machine Learning scores to well-calibrated prediction estimates that can be interpreted as probability estimates. The implemented BBQ (Bayes Binning in Quantiles) model is taken from Naeini (2015, ISBN:0-262-51129-0). Please cite this paper: Schwarz J and Heider D, Bioinformatics 2019, 35(14):2458-2465.
Packaged: 2019-08-19 12:29:09 UTC; dominikheider