Last data update: 2014.03.03
|
R: Compute the receiver operating characteristic (ROC) curve.
Compute the receiver operating characteristic (ROC) curve.
Description
This function computes the receiver operating
characteristic (ROC) curve required for the auc
function and the plot function.
Usage
roc(predictions, labels)
Arguments
predictions |
A numeric vector of classification
probabilities (confidences, scores) of the positive
event.
|
labels |
A factor of observed class labels
(responses) with the only allowed values {0,1}.
|
Value
A list containing the following elements:
cutoffs |
A numeric vector of threshold values
|
fpr |
A numeric vector of false positive rates
corresponding to the threshold values
| tpr |
A
numeric vector of true positive rates corresponding to
the threshold values
|
Author(s)
Authors: Michel Ballings and Dirk Van den Poel,
Maintainer: Michel.Ballings@UGent.be
References
Ballings, M., Van den Poel, D., Threshold Independent
Performance Measures for Probabilistic Classifcation
Algorithms, Forthcoming.
See Also
sensitivity , specificity ,
accuracy , roc ,
auc , plot
Examples
data(churn)
roc(churn$predictions,churn$labels)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(AUC)
AUC 0.3.0
Type AUCNews() to see the change log and ?AUC to get an overview.
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/AUC/roc.Rd_%03d_medium.png", width=480, height=480)
> ### Name: roc
> ### Title: Compute the receiver operating characteristic (ROC) curve.
> ### Aliases: roc
>
> ### ** Examples
>
> data(churn)
>
> roc(churn$predictions,churn$labels)
$cutoffs
[1] 1.000 1.000 0.972 0.968 0.964 0.960 0.932 0.910 0.908 0.902 0.896 0.890
[13] 0.882 0.878 0.866 0.862 0.856 0.840 0.812 0.800 0.784 0.770 0.760 0.758
[25] 0.750 0.748 0.740 0.734 0.714 0.712 0.698 0.694 0.682 0.676 0.672 0.664
[37] 0.650 0.648 0.636 0.612 0.596 0.592 0.586 0.568 0.564 0.556 0.544 0.542
[49] 0.534 0.504 0.500 0.492 0.474 0.472 0.458 0.442 0.436 0.430 0.428 0.426
[61] 0.416 0.410 0.406 0.392 0.390 0.388 0.378 0.376 0.374 0.372 0.366 0.364
[73] 0.362 0.360 0.356 0.354 0.352 0.348 0.342 0.336 0.334 0.330 0.326 0.324
[85] 0.316 0.312 0.310 0.304 0.300 0.298 0.294 0.290 0.286 0.284 0.282 0.278
[97] 0.276 0.274 0.268 0.266 0.264 0.262 0.260 0.258 0.256 0.254 0.252 0.250
[109] 0.248 0.246 0.244 0.242 0.236 0.232 0.230 0.228 0.224 0.222 0.216 0.214
[121] 0.212 0.208 0.206 0.204 0.202 0.200 0.198 0.196 0.192 0.190 0.188 0.186
[133] 0.182 0.178 0.176 0.172 0.170 0.168 0.162 0.160 0.158 0.156 0.154 0.152
[145] 0.150 0.148 0.146 0.144 0.142 0.140 0.138 0.136 0.134 0.132 0.130 0.128
[157] 0.126 0.124 0.122 0.120 0.118 0.116 0.114 0.112 0.110 0.108 0.106 0.104
[169] 0.102 0.100 0.098 0.096 0.094 0.092 0.090 0.088 0.086 0.084 0.082 0.080
[181] 0.078 0.076 0.074 0.072 0.070 0.068 0.066 0.064 0.062 0.060 0.058 0.056
[193] 0.054 0.052 0.050 0.048 0.046 0.044 0.042 0.040 0.038 0.036 0.034 0.032
[205] 0.030 0.028 0.026 0.024 0.022 0.020 0.018 0.016 0.014 0.012 0.010 0.008
[217] 0.006 0.004 0.002 0.000
$fpr
[1] 0.000000000 0.002624672 0.003499563 0.003499563 0.003499563 0.003499563
[7] 0.004374453 0.004374453 0.005249344 0.005249344 0.005249344 0.006124234
[13] 0.006999125 0.006999125 0.007874016 0.007874016 0.007874016 0.007874016
[19] 0.008748906 0.008748906 0.008748906 0.008748906 0.010498688 0.011373578
[25] 0.012248469 0.013123360 0.013123360 0.013123360 0.013123360 0.013998250
[31] 0.014873141 0.015748031 0.015748031 0.016622922 0.016622922 0.017497813
[37] 0.019247594 0.020122485 0.021872266 0.023622047 0.024496938 0.024496938
[43] 0.024496938 0.024496938 0.024496938 0.025371829 0.026246719 0.027121610
[49] 0.027996500 0.028871391 0.029746282 0.029746282 0.031496063 0.032370954
[55] 0.033245844 0.034120735 0.034995626 0.034995626 0.034995626 0.034995626
[61] 0.034995626 0.035870516 0.035870516 0.036745407 0.041994751 0.042869641
[67] 0.042869641 0.043744532 0.044619423 0.046369204 0.047244094 0.047244094
[73] 0.048118985 0.048118985 0.048993876 0.050743657 0.050743657 0.053368329
[79] 0.053368329 0.053368329 0.054243220 0.055118110 0.055118110 0.055993001
[85] 0.056867892 0.056867892 0.057742782 0.059492563 0.060367454 0.061242345
[91] 0.062117235 0.062992126 0.063867017 0.064741907 0.065616798 0.069116360
[97] 0.069991251 0.071741032 0.076990376 0.079615048 0.080489939 0.080489939
[103] 0.080489939 0.081364829 0.084864392 0.085739283 0.093613298 0.093613298
[109] 0.097112861 0.097987752 0.100612423 0.102362205 0.103237095 0.104986877
[115] 0.104986877 0.105861767 0.107611549 0.110236220 0.111111111 0.111986002
[121] 0.112860892 0.112860892 0.113735783 0.114610674 0.116360455 0.117235346
[127] 0.117235346 0.118985127 0.119860017 0.121609799 0.124234471 0.125984252
[133] 0.126859143 0.127734033 0.128608924 0.132108486 0.133858268 0.134733158
[139] 0.139107612 0.140857393 0.143482065 0.145231846 0.146106737 0.146981627
[145] 0.152230971 0.154855643 0.156605424 0.158355206 0.161854768 0.164479440
[151] 0.167104112 0.167979003 0.170603675 0.171478565 0.175853018 0.180227472
[157] 0.181977253 0.186351706 0.187226597 0.189851269 0.195100612 0.198600175
[163] 0.199475066 0.200349956 0.202974628 0.206474191 0.209973753 0.211723535
[169] 0.216972878 0.219597550 0.220472441 0.224846894 0.225721785 0.230096238
[175] 0.237095363 0.237095363 0.239720035 0.246719160 0.249343832 0.251968504
[181] 0.257217848 0.260717410 0.261592301 0.265091864 0.269466317 0.276465442
[187] 0.281714786 0.286089239 0.287839020 0.292213473 0.294838145 0.300087489
[193] 0.304461942 0.308836395 0.314085739 0.320209974 0.323709536 0.330708661
[199] 0.334208224 0.337707787 0.342957130 0.346456693 0.352580927 0.356955381
[205] 0.363079615 0.374453193 0.384951881 0.393700787 0.403324584 0.417322835
[211] 0.420822397 0.427821522 0.441819773 0.452318460 0.465441820 0.489063867
[217] 0.523184602 0.559055118 0.619422572 1.000000000
$tpr
[1] 0.0000000 0.1635220 0.1635220 0.1823899 0.1886792 0.2012579 0.2012579
[8] 0.2075472 0.2075472 0.2138365 0.2201258 0.2201258 0.2264151 0.2327044
[15] 0.2327044 0.2389937 0.2452830 0.2515723 0.2515723 0.2578616 0.2641509
[22] 0.2704403 0.3018868 0.3018868 0.3018868 0.3018868 0.3081761 0.3144654
[29] 0.3207547 0.3207547 0.3207547 0.3207547 0.3270440 0.3270440 0.3333333
[36] 0.3333333 0.3333333 0.3333333 0.3333333 0.3333333 0.3333333 0.3396226
[43] 0.3459119 0.3522013 0.3584906 0.3584906 0.3647799 0.3647799 0.3647799
[50] 0.3647799 0.3710692 0.3773585 0.3836478 0.3836478 0.3836478 0.3836478
[57] 0.3836478 0.3899371 0.3962264 0.4025157 0.4150943 0.4150943 0.4213836
[64] 0.4213836 0.4213836 0.4402516 0.4528302 0.4528302 0.4528302 0.4591195
[71] 0.4591195 0.4654088 0.4654088 0.4716981 0.4779874 0.4779874 0.4842767
[78] 0.4842767 0.5031447 0.5094340 0.5094340 0.5157233 0.5220126 0.5220126
[85] 0.5220126 0.5283019 0.5471698 0.5471698 0.5471698 0.5471698 0.5471698
[92] 0.5471698 0.5534591 0.5534591 0.5597484 0.5660377 0.5660377 0.5660377
[99] 0.5660377 0.5660377 0.5660377 0.5723270 0.5786164 0.5786164 0.5849057
[106] 0.5849057 0.5911950 0.6037736 0.6037736 0.6037736 0.6037736 0.6100629
[113] 0.6100629 0.6226415 0.6289308 0.6289308 0.6289308 0.6477987 0.6477987
[120] 0.6477987 0.6477987 0.6540881 0.6540881 0.6603774 0.6603774 0.6603774
[127] 0.6666667 0.6666667 0.6666667 0.6666667 0.6666667 0.6666667 0.6729560
[134] 0.6729560 0.6729560 0.6729560 0.6729560 0.6792453 0.6918239 0.6918239
[141] 0.6981132 0.7044025 0.7106918 0.7106918 0.7169811 0.7169811 0.7169811
[148] 0.7169811 0.7169811 0.7169811 0.7169811 0.7169811 0.7169811 0.7232704
[155] 0.7232704 0.7232704 0.7232704 0.7232704 0.7232704 0.7232704 0.7358491
[162] 0.7358491 0.7358491 0.7358491 0.7484277 0.7484277 0.7484277 0.7547170
[169] 0.7547170 0.7610063 0.7610063 0.7610063 0.7610063 0.7610063 0.7610063
[176] 0.7672956 0.7735849 0.7735849 0.7861635 0.7924528 0.7924528 0.7924528
[183] 0.7987421 0.8050314 0.8113208 0.8176101 0.8238994 0.8238994 0.8238994
[190] 0.8238994 0.8301887 0.8364780 0.8364780 0.8364780 0.8427673 0.8427673
[197] 0.8427673 0.8490566 0.8490566 0.8553459 0.8553459 0.8553459 0.8553459
[204] 0.8553459 0.8553459 0.8553459 0.8616352 0.8742138 0.8805031 0.8867925
[211] 0.8930818 0.8930818 0.8930818 0.8930818 0.8993711 0.9119497 0.9119497
[218] 0.9119497 0.9245283 1.0000000
attr(,"class")
[1] "AUC" "roc"
>
>
>
>
>
> dev.off()
null device
1
>
|