Error in Principal Component Analysis (PCA) matlab

Error in Principal Component Analysis (PCA) matlab. I applied PCA on matlab using my variable fextracted. It is a 22 x 16 array . I only have fextracted as the information. Please help me with the steps to do PCA. Attached are my data (fextracted) and my PCA code. I dont understand what should i do first before using the PCA() function on MATLAB. Ive seen tutorials and read from matlab PCA docs but i did not manage to figure it out.

[nurin noor]

this is my dataset

Answer 1

[Cris LaPierre]

You are getting this error because you have overwritten MATLAB's pca function with your pca.m file. Rename your file, and your call to pca should work.

See here for execution precedence.

[nurin noor]

Hi Cris, thanks for replying. Really appreciate that.

But, apparently, I did not have any file that named pca.m. I want to ask in order to apply this line, do i need to find coeff, score, latent etc seperately first? Because I saw examples on Matlab doc, they only execute this line after loading the data. Not sure am I understood correclty or not. But, even if i used coeff = pca(fextracted) it gives the same error as well. The coedd,score,latent,tsquared,explained have red lines saying "values assigned are unused, recommed to use ~". So i do not now why this function does not work.

[coeff,score,latent,tsquared,explained] = pca(fextracted);

[Cris LaPierre]

The error message suggests otherwise. Run the following code in the command window

which pca

The result should be something like this: C:\Program Files\MATLAB\R2021a\toolbox\stats\stats\pca.m

Your syntax is correct.

fextracted = rand(22,16);
[coeff,score,latent,tsquared,explained] = pca(fextracted)

coeff = 16×16

-0.0414 0.4172 0.1205 0.2871 0.6193 -0.0735 0.1129 0.1205 0.1097 0.2141 0.0162 0.3444 0.0827 -0.1396 -0.2588 0.2025 -0.2079 0.0292 0.1624 0.5370 -0.2892 0.0452 0.1042 -0.0634 -0.2043 0.2314 0.3456 0.2450 0.0994 -0.1214 0.4364 -0.2254 -0.1059 -0.1846 0.2349 -0.0497 -0.1560 -0.0855 0.4983 0.3462 -0.2047 0.3313 0.0175 -0.3634 -0.0127 -0.0893 -0.1031 0.4410 0.4788 0.0664 -0.2710 0.1164 -0.3339 -0.0306 -0.0870 0.1993 0.0728 0.0753 -0.1985 0.0602 0.4072 -0.5384 -0.0948 0.0333 0.1765 0.3922 0.0863 -0.2889 0.0492 -0.3856 0.0676 -0.0057 0.1444 -0.2174 0.5058 -0.2350 0.2481 -0.0124 0.3428 0.1003 0.3360 -0.2255 0.0197 0.2778 -0.0181 0.0308 0.1925 -0.3264 0.6195 0.1211 -0.0611 -0.0089 -0.1684 0.1507 0.2419 0.3193 -0.4205 0.0812 0.1869 0.0098 -0.1779 -0.2231 0.0484 0.0416 0.5401 0.1567 -0.2317 -0.1885 0.3183 0.0822 -0.1787 -0.3881 0.1167 -0.0461 0.3125 -0.4395 -0.0251 0.4876 -0.1637 -0.1195 0.0395 0.4076 0.1500 0.2140 0.3878 0.1460 -0.0056 0.0791 -0.2565 -0.0794 0.1934 0.1726 0.0759 0.2987 -0.4755 0.4428 0.2267 -0.2773 -0.0164 -0.1648 0.0334 -0.1443 0.2661 0.3083 -0.0051 -0.3974 0.0119 -0.2117 -0.1039 -0.4173 -0.1098 0.3844 0.2014 0.0472 0.2511 0.5553 -0.1852 0.0164 -0.0597 -0.0034

score = 22×16

0.5916 0.3959 -0.0283 0.3969 -0.3703 -0.2739 0.1248 -0.1741 -0.2166 -0.3241 0.2682 0.0876 0.2363 0.0172 -0.0428 -0.0409 -0.5745 0.3889 0.7649 0.1216 0.0371 0.1386 -0.2615 -0.2539 0.1048 0.4315 -0.0601 -0.0760 0.1336 -0.0508 -0.0344 -0.0456 -0.5343 0.0964 -0.3965 0.1531 0.5716 -0.0529 0.1151 0.1186 -0.0198 -0.1760 -0.2102 -0.0179 0.1872 0.2434 0.0357 0.0464 0.3658 0.1188 -0.0745 -0.0959 0.3265 0.1423 -0.1210 0.3631 0.6778 -0.0864 0.0085 0.0573 -0.0693 -0.0345 -0.0540 -0.0340 -1.1158 0.1176 0.0473 0.0949 -0.3773 -0.3859 0.1984 -0.1899 0.1312 -0.1197 0.0049 0.0914 -0.1122 -0.0657 0.0826 0.0206 0.2315 -0.2773 0.5269 -0.2486 0.6571 -0.0102 0.3536 -0.1562 -0.0260 0.0068 0.4174 -0.0323 -0.0993 -0.0246 0.0208 0.0606 -0.3856 0.3658 -0.3582 -0.3215 -0.0401 0.6392 0.1356 -0.4788 0.2512 -0.0378 0.2407 0.1402 0.0733 0.0661 0.0123 -0.0255 0.6539 -0.0443 0.4341 -0.0771 0.0258 -0.2478 -0.2313 -0.1191 0.1442 -0.2703 0.0118 -0.2130 0.0784 -0.0916 -0.0221 0.0730 -0.2626 0.5914 0.4794 0.0879 -0.0430 -0.3025 -0.0907 0.3458 0.1498 -0.2271 -0.1490 0.0244 -0.0961 0.0940 -0.0467 -0.0369 -0.2414 -1.2151 0.3395 -0.1321 -0.2833 -0.1413 0.4139 -0.2173 0.0041 0.0395 -0.1649 0.0482 -0.0423 0.1210 -0.1394 -0.0196

latent = 16×1

0.2674 0.2029 0.1497 0.1367 0.1084 0.0874 0.0819 0.0726 0.0523 0.0413

tsquared = 22×1

16.7472 15.6788 16.8153 14.5799 12.7046 16.2672 15.7190 12.3457 11.2392 18.7158

explained = 16×1

20.6980 15.7046 11.5873 10.5788 8.3876 6.7649 6.3364 5.6231 4.0458 3.1998

[nurin noor]

Hi Chris!!

Thnak you so much!! It works really well. I mislook, there is a file name pca.m . I did not notice it earlier.