header 1 = chunk

header 2

Cỡ chữ 10 cỡ chữ 1 chữ màu xanh chữ màu đỏ chữ màu vàng 

letter.recognition <- read.csv("/cloud/project/Data/letter-recognition.data", header=FALSE)
letters <- letter.recognition
str(letters)
## 'data.frame':    20000 obs. of  17 variables:
##  $ V1 : chr  "T" "I" "D" "N" ...
##  $ V2 : int  2 5 4 7 2 4 4 1 2 11 ...
##  $ V3 : int  8 12 11 11 1 11 2 1 2 15 ...
##  $ V4 : int  3 3 6 6 3 5 5 3 4 13 ...
##  $ V5 : int  5 7 8 6 1 8 4 2 4 9 ...
##  $ V6 : int  1 2 6 3 1 3 4 1 2 7 ...
##  $ V7 : int  8 10 10 5 8 8 8 8 10 13 ...
##  $ V8 : int  13 5 6 9 6 8 7 2 6 2 ...
##  $ V9 : int  0 5 2 4 6 6 6 2 2 6 ...
##  $ V10: int  6 4 6 6 6 9 6 2 6 2 ...
##  $ V11: int  6 13 10 4 6 5 7 8 12 12 ...
##  $ V12: int  10 3 3 4 5 6 6 2 4 1 ...
##  $ V13: int  8 9 7 10 9 6 6 8 8 9 ...
##  $ V14: int  0 2 3 6 1 0 2 1 1 8 ...
##  $ V15: int  8 8 7 10 7 8 8 6 6 1 ...
##  $ V16: int  0 4 3 2 5 9 7 2 1 1 ...
##  $ V17: int  8 10 9 8 10 7 10 7 7 8 ...

installing package

#install.packages("kernlab")

library("kernlab")
colnames(letters) <- c(
  V1 = "letter",
  V2 = "xbox",
  V3 = "ybox",
  V4 = "width",   
  V5 = "height",  
  V6 = "onpix",
  V7= "xbar",  
  V8 = "ybar",     
  V9 = "x2bar",    
  V10 = "y2bar",    
  V11 = "xybar",
  V12 = "x2ybar",   
  V13 = "xy2bar",  
  V14 = "xedge",  
  V15 = "xedgeycor",
  V16 = "yedge",
  V17 = "yedgexcor"
  )

letters$letter <- as.factor(letters$letter)
str(letters)
## 'data.frame':    20000 obs. of  17 variables:
##  $ letter   : Factor w/ 26 levels "A","B","C","D",..: 20 9 4 14 7 19 2 1 10 13 ...
##  $ xbox     : int  2 5 4 7 2 4 4 1 2 11 ...
##  $ ybox     : int  8 12 11 11 1 11 2 1 2 15 ...
##  $ width    : int  3 3 6 6 3 5 5 3 4 13 ...
##  $ height   : int  5 7 8 6 1 8 4 2 4 9 ...
##  $ onpix    : int  1 2 6 3 1 3 4 1 2 7 ...
##  $ xbar     : int  8 10 10 5 8 8 8 8 10 13 ...
##  $ ybar     : int  13 5 6 9 6 8 7 2 6 2 ...
##  $ x2bar    : int  0 5 2 4 6 6 6 2 2 6 ...
##  $ y2bar    : int  6 4 6 6 6 9 6 2 6 2 ...
##  $ xybar    : int  6 13 10 4 6 5 7 8 12 12 ...
##  $ x2ybar   : int  10 3 3 4 5 6 6 2 4 1 ...
##  $ xy2bar   : int  8 9 7 10 9 6 6 8 8 9 ...
##  $ xedge    : int  0 2 3 6 1 0 2 1 1 8 ...
##  $ xedgeycor: int  8 8 7 10 7 8 8 6 6 1 ...
##  $ yedge    : int  0 4 3 2 5 9 7 2 1 1 ...
##  $ yedgexcor: int  8 10 9 8 10 7 10 7 7 8 ...
letters_train <- letters[1:16000,]
letters_test <- letters[16001:20000,]
letter_classifier <- ksvm(letter ~ . , data = letters_train, kernel = "vanilladot") # kernel = "vanilladot" is shape of kernel in this case is linear
##  Setting default kernel parameters
#letter_classifier ##dài quá
letter_predictions <- predict(letter_classifier, letters_test)
letter_predictions[1:100]
##   [1] U N V X N H E Y G E N B G L G W M D Y R P D E W D S R G V R D J C I T C N
##  [38] M B U R A A Q Q H K G S A J G W N H L B E Y J N S Z Q D T L G P K W H W A
##  [75] H T I F I D T R Z I D F C S C B B N E D U L P C N F
## Levels: A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
#table(letter_predictions, letters_test$letter)
agreement <- letter_predictions == letters_test$letter
table(agreement)
## agreement
## FALSE  TRUE 
##   643  3357
prop.table(table(agreement))
## agreement
##   FALSE    TRUE 
## 0.16075 0.83925
letter_classifier_rbf <- ksvm(letter ~ ., data = letters_train, kernel = "rbfdot") # thay đổi kernel = cách khác 
letter_predictions_rbf <- predict(letter_classifier_rbf,
 letters_test) # check thôi
agreement_rbf <- letter_predictions_rbf == letters_test$letter
table(agreement_rbf) # so sánh 
## agreement_rbf
## FALSE  TRUE 
##   278  3722
prop.table(table(agreement_rbf)) # tính % của bảng 
## agreement_rbf
##  FALSE   TRUE 
## 0.0695 0.9305