Convert glmnet::cv.glmnet to data.frame
Arguments
- model
glmnet::cv.glmnetinstance- data
original dataset, if needed
- ...
other arguments passed to methods
Examples
if (requireNamespace("survival", quietly = TRUE)) {
fortify(glmnet::cv.glmnet(data.matrix(Orange[-3]), data.matrix(Orange[3])))
}
#> lambda cvm cvup cvlo nz
#> s0 3.94663432 3494.1504 3934.6490 3053.6518 0
#> s1 3.85360057 3082.7509 3488.9887 2676.5131 1
#> s2 3.76056683 2658.1956 3009.0991 2307.2921 1
#> s3 3.66753309 2305.5001 2611.7507 1999.2495 1
#> s4 3.57449935 2012.4835 2282.8287 1742.1383 1
#> s5 3.48146561 1769.0314 2010.5897 1527.4732 1
#> s6 3.38843187 1566.7451 1785.2652 1348.2249 1
#> s7 3.29539813 1398.6502 1598.7371 1198.5632 1
#> s8 3.20236439 1258.9552 1444.2685 1073.6419 1
#> s9 3.10933064 1142.8508 1316.2794 969.4222 1
#> s10 3.01629690 1046.2953 1210.1185 882.4721 1
#> s11 2.92326316 963.0735 1119.6651 806.4820 1
#> s12 2.83022942 875.1785 1027.5650 722.7921 2
#> s13 2.73719568 777.6329 923.1362 632.1296 2
#> s14 2.64416194 688.4859 823.0013 553.9704 2
#> s15 2.55112820 614.1135 738.5415 489.6855 2
#> s16 2.45809446 552.5777 668.1620 436.9934 2
#> s17 2.36506072 501.6803 609.5111 393.8496 2
#> s18 2.27202697 459.5983 560.6379 358.5588 2
#> s19 2.17899323 424.8195 519.9219 329.7172 2
#> s20 2.08595949 396.0899 486.0156 306.1642 2
#> s21 1.99292575 372.3696 457.7968 286.9424 2
#> s22 1.89989201 352.7964 434.3298 271.2630 2
#> s23 1.80685827 336.6556 414.8333 258.4779 2
#> s24 1.71382453 323.3547 398.6538 248.0555 2
#> s25 1.62079079 312.4026 385.2447 239.5606 2
#> s26 1.52775705 303.3927 374.1478 232.6376 2
#> s27 1.43472330 295.9877 364.9792 226.9963 2
#> s28 1.34168956 289.9086 357.4171 222.4001 2
#> s29 1.24865582 284.9241 351.1918 218.6563 2
#> s30 1.15562208 280.8427 346.0774 215.6081 2
#> s31 1.06258834 277.5062 341.8849 213.1275 2
#> s32 0.96955460 274.7834 338.4564 211.1105 2
#> s33 0.87652086 272.5660 335.6600 209.4720 2
#> s34 0.78348712 270.7643 333.3858 208.1428 2
#> s35 0.69045338 269.3043 331.5421 207.0664 2
#> s36 0.59741963 268.1247 330.0529 206.1964 2
#> s37 0.50438589 267.1750 328.8551 205.4950 2
#> s38 0.41135215 266.4137 327.8961 204.9313 2
#> s39 0.31831841 265.8063 327.1326 204.4799 2
#> s40 0.22528467 265.3244 326.5287 204.1201 2
#> s41 0.13225093 264.9448 326.0550 203.8347 2
#> s42 0.03921719 264.6483 325.6868 203.6098 2
#> s43 -0.05381655 264.4191 325.4043 203.4340 2
#> s44 -0.14685029 264.2444 325.1907 203.2980 2
#> s45 -0.23988404 264.1134 325.0327 203.1941 2
#> s46 -0.33291778 264.0174 324.9190 203.1159 2
#> s47 -0.42595152 263.9495 324.8406 203.0584 2
#> s48 -0.51898526 263.9038 324.7901 203.0175 2
#> s49 -0.61201900 263.8756 324.7616 202.9896 2
#> s50 -0.70505274 263.8610 324.7500 202.9720 2
#> s51 -0.79808648 263.8569 324.7514 202.9625 2
#> s52 -0.89112022 263.8609 324.7627 202.9592 2
#> s53 -0.98415396 263.8709 324.7812 202.9607 2
#> s54 -1.07718771 263.8854 324.8050 202.9657 2
#> s55 -1.17022145 263.9029 324.8324 202.9734 2
#> s56 -1.26325519 263.9225 324.8620 202.9830 2
#> s57 -1.35628893 263.9237 324.8746 202.9727 2