# You can write R code here and then click "Run" to run it on our platform

library(readr)
library(randomForest)


# The competition datafiles are in the directory ../input
# Read competition data files:
train <- read_csv("../input/train.csv")
test <- read_csv("../input/test.csv")


#creating random forest model

labels <- as.factor(train[,1])
labels <- as.data.frame(labels)
labels <- labels[101:42000,]
testlabels <- as.data.frame(as.factor(train[,1]))
testlabels <- as.data.frame(testlabels)

train.var <- train[,-1]
test.var <- train.var[1:100,]
train.var <- train.var[101:42000,]

rf.bench <- randomForest(train.var,labels, ntree=100)

results <- predict(rf.bench,test.var)
r <- as.data.frame(results)
t <- cbind(r,testlabels)

library(png)

top10 <- train[1:100,]
top.pix <- top10[,-1]

#check one of the results between 1-100

mf <- matrix(nrow=28)
start = 32
end = start+8
for(i in start:end){
  
testlabels[i,]
row <- unlist(top.pix[i,])
m <- t(matrix(1-row/256, nrow=28))
mf <- cbind(mf,m)
}
r[start:end,]
writePNG(mf, "number.png")

img <- readPNG("number.png")
grid::grid.raster(img)