R में PCA करना

R में Data Science के लिए Linear Algebra

Eric Eager

Data Scientist at Pro Football Focus

NFL Combine डेटा

head(select(combine, height:shuttle))
  height weight forty vertical bench broad_jump three_cone shuttle
1     71    192  4.38     35.0    14        127       6.71    3.98
2     73    298  5.34     26.5    27         99       7.81    4.71
3     77    256  4.67     31.0    17        113       7.34    4.38
4     74    198  4.34     41.0    16        131       6.56    4.03
5     76    257  4.87     30.0    20        118       7.12    4.23
6     78    262  4.60     38.5    18        128       7.53    4.48
R में Data Science के लिए Linear Algebra

NFL Combine डेटा

prcomp(A)
Standard deviations (1, .., p=8):
[1] 46.7720885  6.6356959  4.7108443  2.2950226  1.6430770  0.2513368  0.1216908  0.1143365

Rotation (n x k) = (8 x 8):
                    PC1          PC2           PC3           PC4          PC5          PC6           PC7           PC8
height      0.042047079 -0.061885367  0.1454490039 -0.1040556410 -0.980792060  0.020679696 -6.155636e-03  0.0008055445
weight      0.980711529 -0.130912788  0.1270100265  0.0193388930  0.066908382 -0.008423587  6.988341e-04  0.0036087841
forty       0.006112061  0.012525260  0.0025260713 -0.0021291637  0.004096693  0.152469227 -2.539868e-01 -0.9549983725
vertical   -0.062926466 -0.333556369  0.0398922845  0.9366594549 -0.074901137  0.012214516  7.045063e-03 -0.0070051256
bench       0.088291423 -0.313533433 -0.9363461471 -0.0745692157 -0.107188391  0.009167322 -8.604309e-05 -0.0048308793
broad_jump -0.156742686 -0.876925849  0.2904565302 -0.3252903706  0.126494599  0.013753112 -2.187651e-03 -0.0076907609
three_cone  0.007468520  0.014691994  0.0009057581  0.0003320888  0.020902644  0.894560357 -3.743559e-01  0.2427137770
shuttle     0.004518826  0.009863931  0.0023111814 -0.0094052914  0.004010629  0.419039274  8.917710e-01 -0.1700673446
R में Data Science के लिए Linear Algebra

NFL Combine डेटा

summary(prcomp(A))
Importance of components:
                           PC1     PC2     PC3     PC4     PC5     PC6     PC7     PC8
Standard deviation     46.7721 6.63570 4.71084 2.29502 1.64308 0.25134 0.12169 0.11434
Proportion of Variance  0.9672 0.01947 0.00981 0.00233 0.00119 0.00003 0.00001 0.00001
Cumulative Proportion   0.9672 0.98663 0.99644 0.99877 0.99996 0.99999 0.99999 1.00000
R में Data Science के लिए Linear Algebra
head(prcomp(A)$x[, 1:2])
            PC1        PC2
[1,] -62.005067  -2.654645
[2,]  48.123290   6.693433
[3,]   3.732016   1.283046
[4,] -56.823742  -9.764098
[5,]   4.213670  -3.779862
[6,]   6.924978 -15.530509
head(cbind(combine[, 1:4], prcomp(A)$x[, 1:2]))
             player position       school year        PC1        PC2
1   Jaire Alexander       CB   Louisville 2018 -62.005067  -2.654645
2       Brian Allen        C Michigan St. 2018  48.123290   6.693433
3      Mark Andrews       TE     Oklahoma 2018   3.732016   1.283046
4         Troy Apke        S     Penn St. 2018 -56.823742  -9.764098
5 Dorance Armstrong     EDGE       Kansas 2018   4.213670  -3.779862
6         Ade Aruna       DE       Tulane 2018   6.924978 -15.530509
R में Data Science के लिए Linear Algebra

PCA के बाद क्या करें

  • Data wrangling/quality control
  • Data visualization
  • Unsupervised learning (clustering)
  • Supervised learning (for prediction or explanation)
  • Much more!
R में Data Science के लिए Linear Algebra

उदाहरण - Data Visualization

R में Data Science के लिए Linear Algebra

अभ्यास करते हैं!

R में Data Science के लिए Linear Algebra

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