Example Iris Data

data(iris)
library(ggplot2)
names(iris)
## [1] "Sepal.Length" "Sepal.Width"  "Petal.Length" "Petal.Width" 
## [5] "Species"
table(iris$Species)
## 
##     setosa versicolor  virginica 
##         50         50         50

Split the data

library(caret)
## Loading required package: lattice
inTrain<- createDataPartition(y=iris$Species,p=0.7,list=F)
training<- iris[inTrain,]
testing<- iris[-inTrain,]

Build predictions

modlda= train(Species~.,data=training,method="lda") #Linear discriminant analysis
## Loading required package: MASS
modnb=train(Species~.,data=training,method="nb") #Naive Bayes 
## Loading required package: klaR
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 3,4,6,10,12,13,14,15,19,21,22,26,28,33,34,44,46,49,54,55,57,58,60,63,66,73,75,84,85,87,88,92,95,96,102,104,105
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 3,4,6,10,12,13,14,15,19,21,22,26,28,33,34,44,46,49,54,55,57,58,60,63,66,73,75,84,85,87,88,92,95,96,102,104,105
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 4,6,8,9,10,11,17,18,23,25,27,28,32,34,36,39,50,55,57,58,59,64,74,77,80,82,84,89,90,92,95,102,104
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 4,6,8,9,10,11,17,18,23,25,27,28,32,34,36,39,50,55,57,58,59,64,74,77,80,82,84,89,90,92,95,102,104
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 4,5,8,11,12,15,16,18,19,20,21,24,26,30,37,39,40,46,48,51,59,61,62,64,67,68,72,73,74,77,78,79,81,84,86,96,99,101,105
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 4,5,8,11,12,15,16,18,19,20,21,24,26,30,37,39,40,46,48,51,59,61,62,64,67,68,72,73,74,77,78,79,81,84,86,96,99,101,105
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 2,8,11,12,13,16,17,18,22,25,29,35,39,42,45,49,50,52,54,55,56,57,59,62,65,66,72,82,83,89,90,91,96,97,101,102
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 2,8,11,12,13,16,17,18,22,25,29,35,39,42,45,49,50,52,54,55,56,57,59,62,65,66,72,82,83,89,90,91,96,97,101,102
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 2,8,9,12,14,19,21,24,28,34,37,38,40,44,45,51,56,65,67,77,79,81,83,84,86,87,90,94,96,100,101,104
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 2,8,9,12,14,19,21,24,28,34,37,38,40,44,45,51,56,65,67,77,79,81,83,84,86,87,90,94,96,100,101,104
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 3,4,6,8,12,13,17,19,23,24,26,28,30,34,36,38,39,43,47,48,49,51,53,54,56,57,60,63,64,68,72,73,75,81,82,86,88,90,93,98,103
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 3,4,6,8,12,13,17,19,23,24,26,28,30,34,36,38,39,43,47,48,49,51,53,54,56,57,60,63,64,68,72,73,75,81,82,86,88,90,93,98,103
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 2,4,6,7,10,12,13,22,24,25,27,30,31,32,41,44,46,48,51,53,56,57,61,67,69,75,76,80,84,85,87,88,91,94,96,98,100,102,105
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 2,4,6,7,10,12,13,22,24,25,27,30,31,32,41,44,46,48,51,53,56,57,61,67,69,75,76,80,84,85,87,88,91,94,96,98,100,102,105
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 2,3,4,5,6,9,11,12,15,20,24,26,28,34,35,37,40,41,45,46,49,51,58,60,64,65,68,69,73,77,78,79,84,87,90,92,105
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 2,3,4,5,6,9,11,12,15,20,24,26,28,34,35,37,40,41,45,46,49,51,58,60,64,65,68,69,73,77,78,79,84,87,90,92,105
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 2,3,6,12,14,18,19,20,23,26,32,34,36,37,39,40,47,48,50,58,59,63,64,65,72,75,78,79,81,83,85,87,89,94,96,98,103,104
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 2,3,6,12,14,18,19,20,23,26,32,34,36,37,39,40,47,48,50,58,59,63,64,65,72,75,78,79,81,83,85,87,89,94,96,98,103,104
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 7,9,11,12,13,16,17,19,23,26,32,34,42,43,44,45,47,48,54,58,59,60,62,63,66,71,73,74,75,76,78,79,84,86,88,89,92,93,97,100,101,103
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 7,9,11,12,13,16,17,19,23,26,32,34,42,43,44,45,47,48,54,58,59,60,62,63,66,71,73,74,75,76,78,79,84,86,88,89,92,93,97,100,101,103
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 3,6,8,9,10,17,19,21,23,25,26,28,31,36,38,40,43,44,46,50,58,63,66,67,75,77,78,80,85,87,89,90,93,94,98,99,101,102,104
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 3,6,8,9,10,17,19,21,23,25,26,28,31,36,38,40,43,44,46,50,58,63,66,67,75,77,78,80,85,87,89,90,93,94,98,99,101,102,104
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 3,5,8,9,11,13,15,17,19,20,24,25,26,27,29,31,32,34,36,37,41,47,51,55,57,60,62,64,66,67,68,71,72,73,76,80,81,83,86,88,92,93,97,100,102
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 3,5,8,9,11,13,15,17,19,20,24,25,26,27,29,31,32,34,36,37,41,47,51,55,57,60,62,64,66,67,68,71,72,73,76,80,81,83,86,88,92,93,97,100,102
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 2,4,5,7,10,14,18,22,24,30,32,35,36,37,45,48,49,51,53,55,61,64,65,66,69,77,78,82,85,87,88,91,94,96,99,100,103
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 2,4,5,7,10,14,18,22,24,30,32,35,36,37,45,48,49,51,53,55,61,64,65,66,69,77,78,82,85,87,88,91,94,96,99,100,103
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 5,7,10,11,12,18,23,24,26,28,29,30,32,33,35,37,44,49,50,52,54,57,60,61,63,64,66,68,73,74,76,77,80,81,83,89,90,99
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 5,7,10,11,12,18,23,24,26,28,29,30,32,33,35,37,44,49,50,52,54,57,60,61,63,64,66,68,73,74,76,77,80,81,83,89,90,99
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 2,5,7,8,13,14,18,22,23,24,27,29,35,37,40,44,46,48,49,51,54,59,60,62,63,64,66,68,70,75,80,84,86,87,90,92,93,95,96,99,101,104
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 2,5,7,8,13,14,18,22,23,24,27,29,35,37,40,44,46,48,49,51,54,59,60,62,63,64,66,68,70,75,80,84,86,87,90,92,93,95,96,99,101,104
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 6,8,17,20,22,24,26,32,39,41,42,45,47,51,52,56,58,60,63,64,67,68,73,75,77,78,81,84,86,87,88,90,94,96,99,103
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 6,8,17,20,22,24,26,32,39,41,42,45,47,51,52,56,58,60,63,64,67,68,73,75,77,78,81,84,86,87,88,90,94,96,99,103
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 3,4,5,9,10,12,15,16,21,22,26,31,33,34,38,41,46,48,50,51,52,57,59,62,64,66,68,70,74,76,80,81,89,90,93,94,96,100,101
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 3,4,5,9,10,12,15,16,21,22,26,31,33,34,38,41,46,48,50,51,52,57,59,62,64,66,68,70,74,76,80,81,89,90,93,94,96,100,101
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 5,6,8,9,14,15,19,21,23,25,27,28,31,33,37,42,43,45,46,48,52,54,55,58,65,68,75,77,78,79,81,87,92,93,95,97,99,100,102,104
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 5,6,8,9,14,15,19,21,23,25,27,28,31,33,37,42,43,45,46,48,52,54,55,58,65,68,75,77,78,79,81,87,92,93,95,97,99,100,102,104
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 6,7,10,12,16,19,22,26,27,31,33,37,40,43,45,47,49,50,52,54,59,64,65,67,68,71,72,80,81,84,87,90,91,96,98,99,101
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 6,7,10,12,16,19,22,26,27,31,33,37,40,43,45,47,49,50,52,54,59,64,65,67,68,71,72,80,81,84,87,90,91,96,98,99,101
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 4,6,8,10,13,15,17,18,26,28,30,32,33,37,39,41,42,44,45,47,49,53,54,57,58,60,63,66,67,69,70,74,76,77,83,94,100,104
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 4,6,8,10,13,15,17,18,26,28,30,32,33,37,39,41,42,44,45,47,49,53,54,57,58,60,63,66,67,69,70,74,76,77,83,94,100,104
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 4,5,7,11,12,14,15,17,19,20,22,23,28,33,35,36,38,39,53,54,59,62,64,66,67,73,74,78,81,82,84,85,87,89,91,97,98,101,104,105
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 4,5,7,11,12,14,15,17,19,20,22,23,28,33,35,36,38,39,53,54,59,62,64,66,67,73,74,78,81,82,84,85,87,89,91,97,98,101,104,105
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 4,5,7,10,11,13,14,16,17,20,26,29,31,34,38,41,42,45,47,49,51,55,57,61,66,70,77,78,79,81,82,84,91,95,96,97,100,103,104,105
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 4,5,7,10,11,13,14,16,17,20,26,29,31,34,38,41,42,45,47,49,51,55,57,61,66,70,77,78,79,81,82,84,91,95,96,97,100,103,104,105
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 2,4,8,9,12,13,16,19,25,27,33,36,37,38,40,41,43,46,49,50,52,53,55,58,59,61,68,71,72,77,80,85,86,88,90,91,95,96,98,100,101,102
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 2,4,8,9,12,13,16,19,25,27,33,36,37,38,40,41,43,46,49,50,52,53,55,58,59,61,68,71,72,77,80,85,86,88,90,91,95,96,98,100,101,102
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 2,3,6,9,10,12,13,14,17,19,24,26,27,31,36,38,40,46,48,55,56,61,62,67,75,77,90,92,93,94,96,99,100,102,104
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 2,3,6,9,10,12,13,14,17,19,24,26,27,31,36,38,40,46,48,55,56,61,62,67,75,77,90,92,93,94,96,99,100,102,104
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 3,4,5,6,9,10,12,13,14,18,21,22,25,28,29,34,36,38,40,43,44,46,48,54,56,65,67,71,72,74,77,81,82,91,98,101,103
## --> row.names NOT used
## Warning in data.row.names(row.names, rowsi, i): some row.names duplicated:
## 3,4,5,6,9,10,12,13,14,18,21,22,25,28,29,34,36,38,40,43,44,46,48,54,56,65,67,71,72,74,77,81,82,91,98,101,103
## --> row.names NOT used
plda= predict(modlda,testing)
pnb=predict(modnb,testing)
table(plda,pnb)
##             pnb
## plda         setosa versicolor virginica
##   setosa         15          0         0
##   versicolor      0         14         0
##   virginica       0          1        15

Comparison of results

equalPredictions= (plda==pnb)
qplot(Petal.Width,Sepal.Width,col=equalPredictions,data=testing)

#It show the 2 algorithm are very simillar, only one different