update for ML.NET 0.3 and fix load problem

mlex.fsx

@@ -6,7 +6,7 @@ open FSharp.Data
 open Microsoft.ML
 
 // 1. Get our data - could be from any source, in this case from a CSV file. This is completely decoupled from the ML library.
-type SentimentData = CsvProvider< @"C:\Users\Isaac\Source\Repos\ml-test\data\imdb_labelled.txt", Separators="\t", HasHeaders=true, IgnoreErrors = true>
+type SentimentData = CsvProvider< const (__SOURCE_DIRECTORY__ + @"\data\imdb_labelled.txt"), Separators="\t", HasHeaders=true, IgnoreErrors = true>
 let imdbData = SentimentData.GetSample()
 
 
@@ -25,15 +25,13 @@ let imdbData = SentimentData.GetSample()
 
 
 // We can easily work with multiple data sources and e.g. concatinate them.
-let yelpData = SentimentData.Load @"C:\Users\Isaac\Source\Repos\ml-test\data\yelp_labelled.txt"
-let amazonCells = SentimentData.Load @"C:\Users\Isaac\Source\Repos\ml-test\data\amazon_cells_labelled.txt"
+let yelpData = SentimentData.Load (__SOURCE_DIRECTORY__ + @"\data\yelp_labelled.txt")
+let amazonCells = SentimentData.Load (__SOURCE_DIRECTORY__ + @"\data\amazon_cells_labelled.txt")
 
 let allData =
-    [ imdbData.Rows
-      yelpData.Rows
-      amazonCells.Rows ]
-    |> Seq.concat
-    |> Seq.toList
+    [ yield! imdbData.Rows
+      yield! yelpData.Rows
+      yield! amazonCells.Rows ]
 
 
 

mlnet.fsx

@@ -2,15 +2,16 @@
 #load @".paket\load\netstandard2.0\main.group.fsx"
 
 open Microsoft.ML
+open Microsoft.ML.Data
 open Microsoft.ML.Runtime.Api
 open Microsoft.ML.Transforms
 open Microsoft.ML.Trainers
 open System
 
-let nativeDirectory = @"C:\Users\Isaac\.nuget\packages\microsoft.ml\0.1.0\runtimes\win-x64\native"
+let nativeDirectory = Environment.GetFolderPath(Environment.SpecialFolder.UserProfile) + @"\.nuget\packages\microsoft.ml\0.3.0\runtimes\win-x64\native"
 Environment.SetEnvironmentVariable("Path", Environment.GetEnvironmentVariable("Path") + ";" + nativeDirectory)
 
-let testDataPath = @"data\imdb_labelled.txt"
+let testDataPath = __SOURCE_DIRECTORY__ + @"\data\imdb_labelled.txt"
 
 type SentimentData() =
     [<Column(ordinal = "0"); DefaultValue>]
@@ -22,8 +23,12 @@ type SentimentPrediction() =
     [<ColumnName "PredictedLabel"; DefaultValue>]
     val mutable Sentiment : bool
 
+let _load = 
+    [ typeof<Microsoft.ML.Runtime.Transforms.TextAnalytics>
+      typeof<Microsoft.ML.Runtime.FastTree.FastTree> ]
+
 let pipeline = LearningPipeline()
-pipeline.Add(TextLoader<SentimentData>(testDataPath, useHeader = false, separator = "tab"))
+pipeline.Add(TextLoader(testDataPath).CreateFrom<SentimentData>(useHeader = false, separator = '\t'))
 pipeline.Add(TextFeaturizer("Features", [| "SentimentText" |]))
 pipeline.Add(FastTreeBinaryClassifier(NumLeaves = 5, NumTrees = 5, MinDocumentsInLeafs = 2))
 
@@ -36,4 +41,5 @@ let predictions =
     |> model.Predict
 
 predictions
-|> Seq.iter(fun p -> printfn "%b" p.Sentiment)
+|> Seq.iter(fun p -> printfn "%b" p.Sentiment)
+

paket.dependencies

@@ -1,4 +1,5 @@
 source https://www.nuget.org/api/v2
+frameworks: netstandard2.0, net461
 generate_load_scripts: true
 storage: none
 nuget FSharp.Data prerelease