github.com/pachyderm/pachyderm@v1.13.4/examples/ml/iris/rstats/iris-train-r-lda/train.R (about)

     1  library(caret)
     2  
     3  # load the CSV file from the local directory
     4  dataset <- read.csv("/pfs/training/iris.csv", header = FALSE)
     5  
     6  # set the column names in the dataset
     7  colnames(dataset) <- c("Sepal.Length",
     8                         "Sepal.Width",
     9                         "Petal.Length",
    10                         "Petal.Width",
    11                         "Species")
    12  
    13  # Run algorithm using 10-fold cross validation
    14  control <- trainControl(method = "cv", number = 10)
    15  metric <- "Accuracy"
    16  
    17  # SVM
    18  set.seed(7)
    19  fit.model <- train(form = Species ~ ., 
    20  	         data = dataset,
    21                   method = "lda", 
    22                   metric = metric, 
    23                   trControl = control)
    24  
    25  # save a summary of this model
    26  sink("/pfs/out/model.txt", append=FALSE, split=FALSE)
    27  print(fit.model)
    28  
    29  # persist the model
    30  save(fit.model, file = "/pfs/out/model.rda")
    31