library(readr)

train<- read_csv("C:/Computational Statistics/Kaggle/Digit Recognition/train (1).csv")

test<- read_csv("C:/Computational Statistics/Kaggle/Digit Recognition/test (1).csv")

train$label=as.factor(train$label)

str(train)


table(train$label)


prop.table(table(train$label))*100

library(lattice)

library(ggplot2)

library(caret)

library(randomForest)

train_train$label=as.factor(train_train$label)

randomfoest1=randomForest(label~. ,data = train,ntree = 50)

pred1=predict(randomfoest,test)

output=data.frame(pred1)

library(xlsx)

write.xlsx(output,file="result.xlsx")