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tengpeng/k-fold CV.r

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  1. @bhoung bhoung created this gist Apr 24, 2014.
    60 changes: 60 additions & 0 deletions k-fold CV.r
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    # original example from Digg Data website (Takashi J. OZAKI, Ph. D.)
    # http://diggdata.in/post/58333540883/k-fold-cross-validation-in-r


    library(plyr)
    library(randomForest)

    data <- iris

    # in this cross validation example, we use the iris data set to
    # predict the Sepal Length from the other variables in the dataset
    # with the random forest model

    k = 5 #Folds

    # sample from 1 to k, nrow times (the number of observations in the data)
    data$id <- sample(1:k, nrow(data), replace = TRUE)
    list <- 1:k

    # prediction and testset data frames that we add to with each iteration over
    # the folds

    prediction <- data.frame()
    testsetCopy <- data.frame()

    #Creating a progress bar to know the status of CV
    progress.bar <- create_progress_bar("text")
    progress.bar$init(k)

    for (i in 1:k){
    # remove rows with id i from dataframe to create training set
    # select rows with id i to create test set
    trainingset <- subset(data, id %in% list[-i])
    testset <- subset(data, id %in% c(i))

    # run a random forest model
    mymodel <- randomForest(trainingset$Sepal.Length ~ ., data = trainingset, ntree = 100)

    # remove response column 1, Sepal.Length
    temp <- as.data.frame(predict(mymodel, testset[,-1]))
    # append this iteration's predictions to the end of the prediction data frame
    prediction <- rbind(prediction, temp)

    # append this iteration's test set to the test set copy data frame
    # keep only the Sepal Length Column
    testsetCopy <- rbind(testsetCopy, as.data.frame(testset[,1]))

    progress.bar$step()
    }

    # add predictions and actual Sepal Length values
    result <- cbind(prediction, testsetCopy[, 1])
    names(result) <- c("Predicted", "Actual")
    result$Difference <- abs(result$Actual - result$Predicted)

    # As an example use Mean Absolute Error as Evalution
    summary(result$Difference)