1. 1. R & Machine Leaning July 6 2015 YoshiharuIkutani @NNCT
2. 2. l l R l R 2 R&MachineLeaning
3. 3. l l R l R 3 R&MachineLeaning
4. 4. l l l Tom Mitchell 4 R&MachineLeaning
5. 5. Tom Mitchell 5 R&MachineLeaning
6. 6. Tom Mitchell TPE E) (P) T 6 R&MachineLeaning
7. 7. Tom Mitchell TPE E PT 7 R&MachineLeaning
8. 8. P(T)(E) E PT 8 R&MachineLeaning
9. 9. l l 9 R&MachineLeaning
10. 10. l 4 1. Classication () 2. Regression () 3. Clustering () 4. Rule Extraction () l 10 R&MachineLeaning
11. 11. l l R l R 11 R&MachineLeaning
12. 12. R l & l ( R&MachineLeaning12 1 (Text)
13. 13. l 1. R http://cran.r-project.org/bin/macosx/ 2. Rstuido http://www.rstudio.com/products/rstudio/ 3. GitHub https://github.com/Yoshiharu-Ikutani/R_machine R&MachineLeaning13
14. 14. CSV l CSV R&MachineLeaning14 >datadata l WorkingDirectoryR_machine Rstudio Ctrl+ShiG+H
15. 15. data l data 1 R&MachineLeaning15 >data[,1] l data 1-32-3 >data[1:3,2:3] l data 1 >data[1,]
16. 16. data l data R&MachineLeaning16 >boxplot(data) l data3 >plot(data[,3],type=l) l data1 >barplot(data[,1])
17. 17. R l n etc. l Python n Scipy, Numpy n Pandas n (R?) R&MachineLeaning17 vs
18. 18. l l R l R 18 R&MachineLeaning
19. 19. R l l R R&MachineLeaning19
20. 20. l 4R 1. (NeuralNetwork.R) 2. (LinerRegression.R) 3. k-means (kmeans.R) 4. (PCA.R) l R&MachineLeaning20
21. 21. l """" l iris n Sepal.Length & Width : n Petal.Length & Width : n Species : R&MachineLeaning21
22. 22. l n R&MachineLeaning22 Sepal.Length Sepal.Width Petal.Length Petal.Width A B C
23. 23. l iris150 n 75 (iris.train) n 75 (iris.test) R&MachineLeaning23 E PT
24. 24. l NeuralNetwork.R R&MachineLeaning24
25. 25. l 4 1. E 2. T 3. P 4. l R&MachineLeaning25