wisc_bc_data <- read.csv("C:/Users/jawii/Downloads/wisc_bc_data.csv",stringsAsFactors = FALSE)
View(wisc_bc_data)
wd<-wisc_bc_data
str(wd)
## 'data.frame': 569 obs. of 32 variables:
## $ id : int 842302 842517 84300903 84348301 84358402 843786 844359 84458202 844981 84501001 ...
## $ diagnosis : chr "M" "M" "M" "M" ...
## $ radius_mean : num 18 20.6 19.7 11.4 20.3 ...
## $ texture_mean : num 10.4 17.8 21.2 20.4 14.3 ...
## $ perimeter_mean : num 122.8 132.9 130 77.6 135.1 ...
## $ area_mean : num 1001 1326 1203 386 1297 ...
## $ smoothness_mean : num 0.1184 0.0847 0.1096 0.1425 0.1003 ...
## $ compactness_mean : num 0.2776 0.0786 0.1599 0.2839 0.1328 ...
## $ concavity_mean : num 0.3001 0.0869 0.1974 0.2414 0.198 ...
## $ concave.points_mean : num 0.1471 0.0702 0.1279 0.1052 0.1043 ...
## $ symmetry_mean : num 0.242 0.181 0.207 0.26 0.181 ...
## $ fractal_dimension_mean : num 0.0787 0.0567 0.06 0.0974 0.0588 ...
## $ radius_se : num 1.095 0.543 0.746 0.496 0.757 ...
## $ texture_se : num 0.905 0.734 0.787 1.156 0.781 ...
## $ perimeter_se : num 8.59 3.4 4.58 3.44 5.44 ...
## $ area_se : num 153.4 74.1 94 27.2 94.4 ...
## $ smoothness_se : num 0.0064 0.00522 0.00615 0.00911 0.01149 ...
## $ compactness_se : num 0.049 0.0131 0.0401 0.0746 0.0246 ...
## $ concavity_se : num 0.0537 0.0186 0.0383 0.0566 0.0569 ...
## $ concave.points_se : num 0.0159 0.0134 0.0206 0.0187 0.0188 ...
## $ symmetry_se : num 0.03 0.0139 0.0225 0.0596 0.0176 ...
## $ fractal_dimension_se : num 0.00619 0.00353 0.00457 0.00921 0.00511 ...
## $ radius_worst : num 25.4 25 23.6 14.9 22.5 ...
## $ texture_worst : num 17.3 23.4 25.5 26.5 16.7 ...
## $ perimeter_worst : num 184.6 158.8 152.5 98.9 152.2 ...
## $ area_worst : num 2019 1956 1709 568 1575 ...
## $ smoothness_worst : num 0.162 0.124 0.144 0.21 0.137 ...
## $ compactness_worst : num 0.666 0.187 0.424 0.866 0.205 ...
## $ concavity_worst : num 0.712 0.242 0.45 0.687 0.4 ...
## $ concave.points_worst : num 0.265 0.186 0.243 0.258 0.163 ...
## $ symmetry_worst : num 0.46 0.275 0.361 0.664 0.236 ...
## $ fractal_dimension_worst: num 0.1189 0.089 0.0876 0.173 0.0768 ...
wd1<-wd[-1]
View(wd1)
wd1$diagnosis
## [1] "M" "M" "M" "M" "M" "M" "M" "M" "M" "M" "M" "M" "M" "M" "M" "M" "M" "M"
## [19] "M" "B" "B" "B" "M" "M" "M" "M" "M" "M" "M" "M" "M" "M" "M" "M" "M" "M"
## [37] "M" "B" "M" "M" "M" "M" "M" "M" "M" "M" "B" "M" "B" "B" "B" "B" "B" "M"
## [55] "M" "B" "M" "M" "B" "B" "B" "B" "M" "B" "M" "M" "B" "B" "B" "B" "M" "B"
## [73] "M" "M" "B" "M" "B" "M" "M" "B" "B" "B" "M" "M" "B" "M" "M" "M" "B" "B"
## [91] "B" "M" "B" "B" "M" "M" "B" "B" "B" "M" "M" "B" "B" "B" "B" "M" "B" "B"
## [109] "M" "B" "B" "B" "B" "B" "B" "B" "B" "M" "M" "M" "B" "M" "M" "B" "B" "B"
## [127] "M" "M" "B" "M" "B" "M" "M" "B" "M" "M" "B" "B" "M" "B" "B" "M" "B" "B"
## [145] "B" "B" "M" "B" "B" "B" "B" "B" "B" "B" "B" "B" "M" "B" "B" "B" "B" "M"
## [163] "M" "B" "M" "B" "B" "M" "M" "B" "B" "M" "M" "B" "B" "B" "B" "M" "B" "B"
## [181] "M" "M" "M" "B" "M" "B" "M" "B" "B" "B" "M" "B" "B" "M" "M" "B" "M" "M"
## [199] "M" "M" "B" "M" "M" "M" "B" "M" "B" "M" "B" "B" "M" "B" "M" "M" "M" "M"
## [217] "B" "B" "M" "M" "B" "B" "B" "M" "B" "B" "B" "B" "B" "M" "M" "B" "B" "M"
## [235] "B" "B" "M" "M" "B" "M" "B" "B" "B" "B" "M" "B" "B" "B" "B" "B" "M" "B"
## [253] "M" "M" "M" "M" "M" "M" "M" "M" "M" "M" "M" "M" "M" "M" "B" "B" "B" "B"
## [271] "B" "B" "M" "B" "M" "B" "B" "M" "B" "B" "M" "B" "M" "M" "B" "B" "B" "B"
## [289] "B" "B" "B" "B" "B" "B" "B" "B" "B" "M" "B" "B" "M" "B" "M" "B" "B" "B"
## [307] "B" "B" "B" "B" "B" "B" "B" "B" "B" "B" "B" "M" "B" "B" "B" "M" "B" "M"
## [325] "B" "B" "B" "B" "M" "M" "M" "B" "B" "B" "B" "M" "B" "M" "B" "M" "B" "B"
## [343] "B" "M" "B" "B" "B" "B" "B" "B" "B" "M" "M" "M" "B" "B" "B" "B" "B" "B"
## [361] "B" "B" "B" "B" "B" "M" "M" "B" "M" "M" "M" "B" "M" "M" "B" "B" "B" "B"
## [379] "B" "M" "B" "B" "B" "B" "B" "M" "B" "B" "B" "M" "B" "B" "M" "M" "B" "B"
## [397] "B" "B" "B" "B" "M" "B" "B" "B" "B" "B" "B" "B" "M" "B" "B" "B" "B" "B"
## [415] "M" "B" "B" "M" "B" "B" "B" "B" "B" "B" "B" "B" "B" "B" "B" "B" "M" "B"
## [433] "M" "M" "B" "M" "B" "B" "B" "B" "B" "M" "B" "B" "M" "B" "M" "B" "B" "M"
## [451] "B" "M" "B" "B" "B" "B" "B" "B" "B" "B" "M" "M" "B" "B" "B" "B" "B" "B"
## [469] "M" "B" "B" "B" "B" "B" "B" "B" "B" "B" "B" "M" "B" "B" "B" "B" "B" "B"
## [487] "B" "M" "B" "M" "B" "B" "M" "B" "B" "B" "B" "B" "M" "M" "B" "M" "B" "M"
## [505] "B" "B" "B" "B" "B" "M" "B" "B" "M" "B" "M" "B" "M" "M" "B" "B" "B" "M"
## [523] "B" "B" "B" "B" "B" "B" "B" "B" "B" "B" "B" "M" "B" "M" "M" "B" "B" "B"
## [541] "B" "B" "B" "B" "B" "B" "B" "B" "B" "B" "B" "B" "B" "B" "B" "B" "B" "B"
## [559] "B" "B" "B" "B" "M" "M" "M" "M" "M" "M" "B"
table(wd1$diagnosis)
##
## B M
## 357 212
prop.table(table(wd1$diagnosis))
##
## B M
## 0.6274165 0.3725835
summary(wd[c("radius_mean", "area_mean", "smoothness_mean")])
## radius_mean area_mean smoothness_mean
## Min. : 6.981 Min. : 143.5 Min. :0.05263
## 1st Qu.:11.700 1st Qu.: 420.3 1st Qu.:0.08637
## Median :13.370 Median : 551.1 Median :0.09587
## Mean :14.127 Mean : 654.9 Mean :0.09636
## 3rd Qu.:15.780 3rd Qu.: 782.7 3rd Qu.:0.10530
## Max. :28.110 Max. :2501.0 Max. :0.16340
normalize<-function(x){
return ((x- min(x))/(max(x)-min(x)))
}
normalize(c(1,2,3,4,5))
## [1] 0.00 0.25 0.50 0.75 1.00
wd_n<-as.data.frame(lapply(wd1[2:31],normalize))
summary(wd_n[c("radius_mean", "area_mean", "smoothness_mean")])
## radius_mean area_mean smoothness_mean
## Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.2233 1st Qu.:0.1174 1st Qu.:0.3046
## Median :0.3024 Median :0.1729 Median :0.3904
## Mean :0.3382 Mean :0.2169 Mean :0.3948
## 3rd Qu.:0.4164 3rd Qu.:0.2711 3rd Qu.:0.4755
## Max. :1.0000 Max. :1.0000 Max. :1.0000
wd1$diagnosis<-factor(wd1$diagnosis,levels= c("B","M"),labels=c("Benign","Malignant"))
str(wd1$diagnosis)
## Factor w/ 2 levels "Benign","Malignant": 2 2 2 2 2 2 2 2 2 2 ...
wd1_train<-wd_n[1:469,]
wd1_test<-wd_n[470:569,]
wd1_train_labels<-wd1[1:469,1]
wd1_test_labels<-wd1[470:569,1]
head(wd1_test_labels)
## [1] Benign Benign Benign Benign Benign Benign
## Levels: Benign Malignant
library(class)
## Warning: package 'class' was built under R version 4.3.3
wd1_test_pred<-knn(train= wd1_train, test = wd1_test,cl=wd1_train_labels, k=21)
wd1_test_pred
## [1] Benign Benign Benign Benign Benign Benign Benign
## [8] Benign Benign Benign Malignant Benign Benign Benign
## [15] Benign Benign Benign Benign Malignant Benign Benign
## [22] Benign Benign Malignant Benign Benign Benign Benign
## [29] Benign Malignant Malignant Benign Malignant Benign Malignant
## [36] Benign Benign Benign Benign Benign Malignant Benign
## [43] Benign Malignant Benign Benign Benign Malignant Malignant
## [50] Benign Benign Benign Malignant Benign Benign Benign
## [57] Benign Benign Benign Benign Benign Benign Benign
## [64] Benign Malignant Benign Malignant Malignant Benign Benign
## [71] Benign Benign Benign Benign Benign Benign Benign
## [78] Benign Benign Benign Benign Benign Benign Benign
## [85] Benign Benign Benign Benign Benign Benign Benign
## [92] Benign Benign Malignant Malignant Malignant Malignant Malignant
## [99] Malignant Benign
## Levels: Benign Malignant
library(gmodels)
## Warning: package 'gmodels' was built under R version 4.3.3
CrossTable(x=wd1_test_labels, y=wd1_test_pred,prop.chisq = FALSE)
##
##
## Cell Contents
## |-------------------------|
## | N |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 100
##
##
## | wd1_test_pred
## wd1_test_labels | Benign | Malignant | Row Total |
## ----------------|-----------|-----------|-----------|
## Benign | 77 | 0 | 77 |
## | 1.000 | 0.000 | 0.770 |
## | 0.975 | 0.000 | |
## | 0.770 | 0.000 | |
## ----------------|-----------|-----------|-----------|
## Malignant | 2 | 21 | 23 |
## | 0.087 | 0.913 | 0.230 |
## | 0.025 | 1.000 | |
## | 0.020 | 0.210 | |
## ----------------|-----------|-----------|-----------|
## Column Total | 79 | 21 | 100 |
## | 0.790 | 0.210 | |
## ----------------|-----------|-----------|-----------|
##
##