I want to make my first app in ML.NET. I bet on Wisconsin Prognostic Breast Cancer Dataset. I generete .csv file by myself. One record of that file looks like this:
B;11.62;18.18;76.38;408.8;0.1175;0.1483;0.102;0.05564;0.1957;0.07255;0.4101;1.74;3.027;27.85;0.01459;0.03206;0.04961;0.01841;0.01807;0.005217;13.36;25.4;88.14;528.1;0.178;0.2878;0.3186;0.1416;0.266;0.0927
And it get 31 diffrent features (columns).
My CancerData.cs looks like this:
class CancerData
{
[Column(ordinal: "0")]
public string Diagnosis;
[Column(ordinal: "1")]
public float RadiusMean;
[Column(ordinal: "2")]
public float TextureMean;
[Column(ordinal: "3")]
public float PerimeterMean;
//.........
[Column(ordinal: "28")]
public float ConcavPointsWorst;
[Column(ordinal: "29")]
public float SymmetryWorst;
[Column(ordinal: "30")]
public float FractalDimensionWorst;
[Column(ordinal: "31", name: "Label")]
public string Label;
}
And CancerPrediction.cs
class CancerPrediction
{
[ColumnName("PredictedLabel")]
public string Diagnosis;
}
My Program.cs :
class Program
{
static void Main(string[] args)
{
PredictionModel<CancerData, CancerPrediction> model = Train();
Evaluate(model);
}
public static PredictionModel<CancerData, CancerPrediction> Train()
{
var pipeline = new LearningPipeline();
pipeline.Add(new TextLoader("Cancer-train.csv").CreateFrom<CancerData>(useHeader: true, separator: ';'));
pipeline.Add(new Dictionarizer(("Diagnosis", "Label")));
pipeline.Add(new ColumnConcatenator(outputColumn: "Features",
"RadiusMean",
"TextureMean",
"PerimeterMean",
//... all of the features
"FractalDimensionWorst"));
pipeline.Add(new StochasticDualCoordinateAscentBinaryClassifier());
pipeline.Add(new PredictedLabelColumnOriginalValueConverter() { PredictedLabelColumn = "PredictedLabel" });
PredictionModel<CancerData, CancerPrediction> model = pipeline.Train<CancerData, CancerPrediction>();
model.WriteAsync(modelPath);
return model;
}
public static void Evaluate(PredictionModel<CancerData, CancerPrediction> model)
{
var testData = new TextLoader("Cancer-test.csv").CreateFrom<CancerData>(useHeader: true, separator: ';');
var evaluator = new ClassificationEvaluator();
ClassificationMetrics metrics = evaluator.Evaluate(model, testData);
var accuracy = Math.Round(metrics.AccuracyMicro, 2);
Console.WriteLine("The accuracy is: " + accuracy);
Console.ReadLine();
}
}
What i get, is:
ArgumentOutOfRangeException: Score column is missing
On ClassificationMetrics metrics = evaluator.Evaluate(model, testData); method.
When i add Score Column in CancerPrediction, i still get the same exception.
I saw that someone have the same problem on StackOverflow but it looks like it is without answer and i cant make a comment on it because i dont have enough reputation. Is it a bug? maybe my data is not prepared properly? Im using ML.NET in ver. 0.5.0
Thanks for any advices!
EDIT1:
When i add into CancerPrediction.cs that line:
class CancerPrediction
{
[ColumnName("PredictedLabel")]
public string PredictedDiagnosis;
[ColumnName("Score")]
public string Score; // => new column!
}
I get an exception:
System.InvalidOperationException: 'Can't bind the IDataView column 'Score' of type 'R4' to field or property 'Score' of type 'System.String'.'
in line:
PredictionModel<CancerData, CancerPrediction> model = pipeline.Train<CancerData, CancerPrediction>();
EDIT2
How it looks:
EDIT3
Change Separator to ',' and load original dataset not prepered by me it still yelling, taht there is no Score, so annoying