Generates a confusin matrix plot out of predicted-labels and labels

• opts

  • normalize : Can be :none (default) or :all and decides if the values in the matrix are counts or percentages.

• hanami-opts Options passed to hanami to control the plot. Can be any of the default hanami substituions keys.

Generates a learning curve.

The functions splits the dataset in a fixed size test set and increasingly larger training sets. A model is trained at each step and evaluated.

Returns a vega lite spec of the learninig curve plot.

• dataset the TMD dataset to use
• train-sizes vector of double from 0 to 1, controlling the sizes of the training data.
• lc-opts
  • k At each step a k cross-validation is done
  • metric-fn the metric to use for evaluation the model
  • loss-or-accuracy If the metric-fn calculates :loss or :accuracy
• hanami-opts Options passed to hanami to control the plot. Can be the default hanami substituions keys or:
  • TRAIN-COLOR: Color used for the train curve (default: blue)
  • TEST-COLOR: Color used for the test curve (default: orange)