mlDotnetIrisPrediction.fs

// Learn more about F# at http://fsharp.org
open Microsoft.ML
open Microsoft.ML.Runtime.Api
open Microsoft.ML.Trainers
open Microsoft.ML.Transforms
open System

//The first four properties are inputs, the label is what you are predicting which is set in training
type IrisData() =
    [<Column("0")>] [<DefaultValue>]
    val mutable public SepalLength: float32
    [<Column("1")>] [<DefaultValue>]
    val mutable public SepalWidth: float32
    [<Column("2")>] [<DefaultValue>] 
    val mutable public PetalLength:float32
    [<Column("3")>] [<DefaultValue>]
    val mutable public PetalWidth:float32
    [<Column("4")>] [<ColumnName("Label")>] [<DefaultValue>]
    val mutable public Label:string

//Result returned from the prediction operation
type IrisPrediction() =
    [<ColumnName("PredictedLabel")>] [<DefaultValue>]
    val mutable public PredictedLabel : string

[<EntryPoint>]
let main argv =
    //Create a pipeline
    let pipeline = new LearningPipeline()
    let dataPath = "iris-data.txt"
    //Loads CSV data
    pipeline.Add(new TextLoader<IrisData>(dataPath,separator = ",")) 
    //Transforms the label into an "enum" because only numbers can be processed during training
    pipeline.Add(new Transforms.Dictionarizer("Label"))
    //Transforms all features into one vector
    pipeline.Add(new Transforms.ColumnConcatenator("Features","SepalLength", "SepalWidth", "PetalLength", "PetalWidth"))
    //applies a learning algorithm
    pipeline.Add(new Trainers.StochasticDualCoordinateAscentClassifier())
    //Transforms the label back into the original text
    pipeline.Add(new Transforms.PredictedLabelColumnOriginalValueConverter(PredictedLabelColumn = "PredictedLabel"))
    //Train the model
    let model = pipeline.Train<IrisData, IrisPrediction>()

    //Initialize the data we hope to test
    let x = IrisData()
    x.SepalLength <- 3.3f
    x.SepalWidth <- 1.6f
    x.PetalLength <- 0.2f
    x.PetalWidth <- 5.1f

    //predict the label from the trained model
    let prediction = model.Predict(x)
    printfn "Predicted flower type is: %s"  prediction.PredictedLabel
    Console.ReadLine () |> ignore
    0 // return an integer exit code