[PDF] Zone AUc

Chapitre II - Zone AUC Section 1 - Nature de l'Utilisation et de l'Occupation des Sols Article AUC 1 - Occupations et Utilisations du Sol interdites Sont interdites

Caractère de la zone AUc: Il s'agit d'une zone destinée à permettre l'extension de l'urbanisation principalement d'habitat, sous forme d'opération d'ensemble

[PDF] Principes de Pharmacocinétique

AUC per os AUC IV AUC = Aire sous la courbe = - si toute la dose administrée PO est AUC × Ke Cl: Clairance du médicament Ke: Constante d'élimination

« La zone « AUc» représente le quartier de la Roulète Aujourd'hui, cette zone d' urbanisation future est considérée comme « stricte » dans la mesure où les voies

[PDF] AUc - Riorges - Riorges

La zone AUc est une zone à urbaniser destinée à une mixité de typologies et de fonctions urbaines, tout en étant à vocation dominante d'habitat L'objectif du

[PDF] DISPOSITIONS APPLICABLES A LA ZONE AUc - Ville de POISSY

421-27 du Code de l'urbanisme et de la délibération n°31 du Conseil Municipal du 27 septembre 2007 II CONDITIONS D'OCCUPATION DU SOL ARTICLE AUC

[PDF] courbe ROC

AUC indique la probabilité pour que la fonction SCORE place un positif devant un négatif (dans le meilleur des cas AUC = 1) Ricco Rakotomalala Tutoriels

[PDF] Régression Logistique sous R - Evaluation du modèle - Courbe

23 mar 2020 · 3 Exercices – Bébés à faible poids – Courbe ROC et AUC 3 1 Importation, modélisation, probabilités d'affectation aux classes 0 Importez le

[PDF] COURS DE PHARMACOCINÉTIQUE - Recherche Clinique Paris

21 nov 2014 · voie ref voie ref e voie testé Dose Dose AUC AUC F Temps Con ce n tra tio n s avec AUC = exposition au médicament dttC AUC 0

[PDF] Zone AUc - Laudun-lArdoise

Chapitre II - Zone AUC Section 1 - Nature de l'Utilisation et de l'Occupation des Sols Article AUC 1 - Occupations et Utilisations du Sol interdites Sont interdites

[PDF] auchan drive comment ça marche

[PDF] auchan drive faq

[PDF] auction

[PDF] audi a4 b9 manuel d utilisation francais pdf

[PDF] audi a6 allroad 2010 brochure

[PDF] audi a6 ambiente

[PDF] audi a6 avant catalogue

[PDF] audi a6 berline occasion

[PDF] audi q3 mmi navigation

[PDF] audience bfm business mediametrie

[PDF] audiovisuel maroc

[PDF] audit comptable et financier cours maroc

[PDF] audit comptable et financier objectifs demarche et techniques

[PDF] audit cours et exercices corrigés

[PDF] audit des systèmes d'information cours

Package 'AUC"

October 12, 2022

TypePackage

TitleThreshold Independent Performance Measures for Probabilistic

Classifiers

Version0.3.2

Date2022-04-04

AuthorMichel Ballings and Dirk Van den Poel

MaintainerMichel Ballings DescriptionVarious functions to compute the area under the curve of selected measures: The area un- der the sensitivity curve (AUSEC), the area under the specificity curve (AUSPC), the area un- der the accuracy curve (AUACC), and the area under the receiver operating characteris- tic curve (AUROC). Support for visualization and partial areas is included.

LicenseGPL (>= 2)

ByteCompiletrue

RoxygenNote7.1.2

EncodingUTF-8

NeedsCompilationno

RepositoryCRAN

Date/Publication2022-04-04 15:40:17 UTC

Rtopics documented:

AUC-package . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 accuracy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 auc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 AUCNews . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 churn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 plot.AUC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 roc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 sensitivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 specificity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Index11

2AUC-packageAUC-packageThreshold independent performance measures for probabilistic classi-

fiers.Description Summary and plotting functions for threshold independent performance measures for probabilistic classifiers.

Details

This package includes functions to compute the area under the curve (functionauc) of selected mea- sures: The area under the sensitivity curve (AUSEC) (functionsensitivity), the area under the specificity curve (AUSPC) (functionspecificity), the area under the accuracy curve (AUACC) (functionaccuracy), and the area under the receiver operating characteristic curve (AUROC) (func- tionroc). The curves can also be visualized using the functionplot. Support for partial areas is provided. Auxiliary code in this package is adapted from theROCRpackage. The measures available in this package are not available in the ROCR package or vice versa (except for the AUROC). As for the AUROC, we adapted theROCRcode to increase computational speed (so it can be used more effectively in objective functions). As a result less funtionality is offered (e.g., averaging cross validation runs). Please use theROCRpackage for that purposes.

Author(s)

Michel Ballings and Dirk Van den Poel, Maintainer:

References

Ballings, M., Van den Poel, D., Threshold Independent Performance Measures for Probabilistic

Classifcation Algorithms, Forthcoming.

Examples

data(churn) auc(roc(churn$predictions,churn$labels)) accuracy3 plot(roc(churn$predictions,churn$labels))accuracyCompute the accuracy curve.Description This function computes the accuracy curve required for theaucfunction and theplotfunction. Usage accuracy(predictions, labels, perc.rank = TRUE)

Arguments

predictionsA numeric vector of classification probabilities (confidences, scores) of the pos- itive event. labelsA factor of observed class labels (responses) with the only allowed values {0,1}. perc.rankA logical. If TRUE (default) the percentile rank of the predictions is used. Value

A list containing the following elements:

cutoffsA numeric vector of threshold values measureA numeric vector of accuracy values corresponding to the threshold values

Author(s)

Authors: Michel Ballings and Dirk Van den Poel, Maintainer:

References

Ballings, M., Van den Poel, D., Threshold Independent Performance Measures for Probabilistic

Classifcation Algorithms, Forthcoming.

Examples

data(churn) accuracy(churn$predictions,churn$labels)

4aucaucCompute the area under the curve of a given performance measure.Description

This function computes the area under the sensitivity curve (AUSEC), the area under the speci- ficity curve (AUSPC), the area under the accuracy curve (AUACC), or the area under the receiver operating characteristic curve (AUROC). Usage auc(x, min = 0, max = 1)

Arguments

orroc mina numeric value between 0 and 1, denoting the cutoff that defines the start of the area under the curve maxa numeric value between 0 and 1, denoting the cutoff that defines the end of the area under the curve Value A numeric value between zero and one denoting the area under the curve

Author(s)

Authors: Michel Ballings and Dirk Van den Poel, Maintainer:

References

Ballings, M., Van den Poel, D., Threshold Independent Performance Measures for Probabilistic

Classifcation Algorithms, Forthcoming.

Examples

data(churn)

AUCNews5

auc(roc(churn$predictions,churn$labels))AUCNewsDisplay the NEWS fileDescription

AUCNewsshows the NEWS file of the AUC package.

Usage

AUCNews()

Value

None.churnChurn dataDescription

churncontains three variables: the churn predictions (probabilities) of two models, and observed churn Usage data(churn)

Format

A data frame with 1302 observations, and 3 variables:predictions,predictions2,churn.

Author(s)

Authors: Michel Ballings and Dirk Van den Poel, Maintainer:

References

Ballings, M., Van den Poel, D., Threshold Independent Performance Measures for Probabilistic

Classifcation Algorithms, Forthcoming.

Examples

data(churn) str(churn)

6plot.AUCplot.AUCPlot the sensitivity, specificity, accuracy and roc curves.Description

This function plots the (partial) sensitivity, specificity, accuracy and roc curves. Usage ## S3 method for class?AUC? plot(x, y = NULL, ..., type = "l", add = FALSE, min = 0, max = 1)

Arguments

orroc yNot used. ...Arguments to be passed to methods, such as graphical parameters. See ?plot typeType of plot. Default is line plot. addLogical. If TRUE the curve is added to an existing plot. If FALSE a new plot is created. mina numeric value between 0 and 1, denoting the cutoff that defines the start of the area under the curve maxa numeric value between 0 and 1, denoting the cutoff that defines the end of the area under the curve

Author(s)

Authors: Michel Ballings and Dirk Van den Poel, Maintainer:

References

Ballings, M., Van den Poel, D., Threshold Independent Performance Measures for Probabilistic

Classifcation Algorithms, Forthcoming.

Examples

data(churn) roc7

plot(roc(churn$predictions,churn$labels))rocCompute the receiver operating characteristic (ROC) curve.Description

This function computes the receiver operating characteristic (ROC) curve required for theaucfunc- tion and theplotfunction. Usage roc(predictions, labels)

Arguments

A list containing the following elements:

cutoffsA numeric vector of threshold values fprA numeric vector of false positive rates corresponding to the threshold values tprA numeric vector of true positive rates corresponding to the threshold values

Author(s)

Authors: Michel Ballings and Dirk Van den Poel, Maintainer:

References

Ballings, M., Van den Poel, D., Threshold Independent Performance Measures for Probabilistic

Classifcation Algorithms, Forthcoming.

Examples

data(churn) roc(churn$predictions,churn$labels)sensitivityCompute the sensitivity curve.Description This function computes the sensitivity curve required for theaucfunction and theplotfunction. Usage sensitivity(predictions, labels, perc.rank = TRUE)

Arguments

A list containing the following elements:

cutoffsA numeric vector of threshold values measureA numeric vector of sensitivity values corresponding to the threshold values

Author(s)

Authors: Michel Ballings and Dirk Van den Poel, Maintainer:

References

Ballings, M., Van den Poel, D., Threshold Independent Performance Measures for Probabilistic

Classifcation Algorithms, Forthcoming.

Examples

data(churn) sensitivity(churn$predictions,churn$labels)specificityCompute the specificity curve.Description This function computes the specificity curve required for theaucfunction and theplotfunction. Usage specificity(predictions, labels, perc.rank = TRUE)

Arguments

A list containing the following elements:

cutoffsA numeric vector of threshold values measureA numeric vector of specificity values corresponding to the threshold values

Author(s)

Authors: Michel Ballings and Dirk Van den Poel, Maintainer:

References

Ballings, M., Van den Poel, D., Threshold Independent Performance Measures for Probabilistic

Classifcation Algorithms, Forthcoming.

Examples

data(churn) Index datasets churn,5 accuracy,2,3 ,3 ,4,6-9

AUC(AUC-package),2

auc,2-4,4 ,6-9

AUC-package,2

AUCNews,5

churn,5 plot,2-4,6-9 plot.AUC,6 roc,2-4,6,7 ,7 ,8,9 sensitivity,2-4,6-8,8 ,9 specificity,2-4,6-9,9 11quotesdbs_dbs49.pdfusesText_49

[PDF] [PDF] Zone AUc - Laudun-lArdoise

Package 'AUC"

October 12, 2022

TypePackage

Classifiers

Version0.3.2

Date2022-04-04

AuthorMichel Ballings and Dirk Van den Poel

LicenseGPL (>= 2)

ByteCompiletrue

RoxygenNote7.1.2

EncodingUTF-8

NeedsCompilationno

RepositoryCRAN

Date/Publication2022-04-04 15:40:17 UTC

Rtopics documented:

Index11

2AUC-packageAUC-packageThreshold independent performance measures for probabilistic classi-

Details

Author(s)

References

Classifcation Algorithms, Forthcoming.

See Also

Examples

Arguments

A list containing the following elements:

Author(s)

References

Classifcation Algorithms, Forthcoming.

See Also

Examples

4aucaucCompute the area under the curve of a given performance measure.Description

Arguments

Author(s)

References

Classifcation Algorithms, Forthcoming.

See Also

Examples

AUCNews5

AUCNewsshows the NEWS file of the AUC package.

AUCNews()

None.churnChurn dataDescription

Format

Author(s)

References

Classifcation Algorithms, Forthcoming.

Examples

6plot.AUCplot.AUCPlot the sensitivity, specificity, accuracy and roc curves.Description

Arguments

Author(s)

References

Classifcation Algorithms, Forthcoming.

See Also

Examples

Arguments

A list containing the following elements:

Author(s)

References

Classifcation Algorithms, Forthcoming.

See Also

8sensitivity

Examples

Arguments

A list containing the following elements:

Author(s)

References

Classifcation Algorithms, Forthcoming.

See Also

Examples

Arguments

A list containing the following elements:

Author(s)

References

Classifcation Algorithms, Forthcoming.

See Also

10specificity

Examples

AUC(AUC-package),2

AUC-package,2

AUCNews,5