github.com/pachyderm/pachyderm@v1.13.4/examples/ml/iris/julia/iris-train-julia-tree/train.jl (about)

     1  using DataFrames
     2  using DecisionTree
     3  using JLD
     4  
     5  # Read the iris data set.
     6  df = readtable(ARGS[1], header = false)
     7  
     8  # Get the features and labels.
     9  features = convert(Array, df[:, 1:4])
    10  labels = convert(Array, df[:, 5])
    11  
    12  # Train decision tree classifier.
    13  model = DecisionTreeClassifier(pruning_purity_threshold=0.9, maxdepth=6)
    14  DecisionTree.fit!(model, features, labels)
    15  
    16  # Save the model.
    17  save(ARGS[2], "model", model)
    18