Multi class predicted label shifted by one.

[Ivanidzo4ka]

public class Digit
{
    [Column("0")] public float Up;

    [Column("1")] public float Middle;

    [Column("2")] public float Bottom;

    [Column("3")] public float UpLeft;
    [Column("4")] public float BottomLeft;
    [Column("5")] public float TopRight;
    [Column("6")] public float BottomRight;

    [Column("7")] [ColumnName("Label")] public float Label;
}

public class DigitPrediction
{
    [ColumnName("PredictedLabel")]
    public uint ExpectedDigit;

    [ColumnName("Score")]
    public float[] Score;
}


var pipeline = new LearningPipeline();
var data = new Digit[]
{
    new Digit { Up = 1, Middle = 0, Bottom = 1, UpLeft = 1, BottomLeft = 1, TopRight = 1, BottomRight = 1, Label = 0 },
    new Digit { Up = 0, Middle = 0, Bottom = 0, UpLeft = 0, BottomLeft = 0, TopRight = 1, BottomRight = 1, Label = 1 },
    new Digit { Up = 1, Middle = 1, Bottom = 1, UpLeft = 0, BottomLeft = 1, TopRight = 1, BottomRight = 0, Label = 2 },
    new Digit { Up = 1, Middle = 1, Bottom = 1, UpLeft = 0, BottomLeft = 0, TopRight = 1, BottomRight = 1, Label = 3 },
    new Digit { Up = 0, Middle = 1, Bottom = 0, UpLeft = 1, BottomLeft = 1, TopRight = 1, BottomRight = 1, Label = 4 },
    new Digit { Up = 1, Middle = 1, Bottom = 1, UpLeft = 1, BottomLeft = 1, TopRight = 0, BottomRight = 1, Label = 5 },
    new Digit { Up = 1, Middle = 1, Bottom = 1, UpLeft = 1, BottomLeft = 1, TopRight = 0, BottomRight = 1, Label = 6 },
    new Digit { Up = 1, Middle = 0, Bottom = 0, UpLeft = 0, BottomLeft = 0, TopRight = 1, BottomRight = 1, Label = 7 },
    new Digit { Up = 1, Middle = 1, Bottom = 1, UpLeft = 1, BottomLeft = 1, TopRight = 1, BottomRight = 1, Label = 8 },
    new Digit { Up = 1, Middle = 1, Bottom = 1, UpLeft = 1, BottomLeft = 0, TopRight = 1, BottomRight = 1, Label = 9 }

};
pipeline.Add(CollectionDataSource.Create(data));
pipeline.Add(new ColumnConcatenator("Features", "Up", "Middle", "Bottom", "UpLeft", "BottomLeft", "TopRight", "BottomRight"));
pipeline.Add(new StochasticDualCoordinateAscentClassifier());
var model = pipeline.Train<Digit, DigitPrediction>();
var prediction = model.Predict(new Digit
{
    Up = 1,
    Middle = 1,
    Bottom = 1,
    UpLeft = 1,
    BottomLeft = 1,
    TopRight = 1,
    BottomRight = 1});

I have this wonderful test, but for ExpectedDigit is shifted by 1. I.e if it predict digit 9, it put 10 into expectedDigit

[Ivanidzo4ka]

slightly related to #226.
@yaeldekel @TomFinley any chance you know why it's +1?

machinelearning/src/Microsoft.ML.Data/Scorers/MultiClassClassifierScorer.cs

Line 569 in 2bbef17

dst = (uint)index + 1;

[Ivanidzo4ka]

same for clustering

machinelearning/src/Microsoft.ML.Data/Scorers/ClusteringScorer.cs

Line 114 in 35b8134

dst = (uint)index + 1;

[TomFinley]

Hi @Ivanidzo4ka ... The output is a key value, and it is important for various reasons that the default value of a key value be undefined, rather than any particular class. So if the "default" clustering were the first class.

We probably ought to have a better story for this. Right now the API does not expose this sort of enumeration "well." A language like R has pretty deep support for this concept in the form of factors. I'm not sure how the API should expose this concept, but it's a fairly central one, so we ought to have a better story than just a uint being surfaced somewhere. (We have docs describing key values, but I wrote that more as code rather than user documentation.)

[Zruty0]

This seems to be a documentation issue: we should document how we handle key types.

And, by the way, this handling has actually changed along the way: as far as I remember, the key values are no longer off by 1, if you use schema comprehension to read the data via AsEnumerable<T>.

[shmoradims]

This is an old issue and seems to have been fixed in 1.0, as seen in this example.