/// <summary>
/// Creates a set of decision variables from input data.
/// </summary>
///
/// <param name="inputs">The input data.</param>
///
/// <returns>An array of <see cref="DecisionVariable"/> objects
/// initialized with the values from the codebook.</returns>
///
public static DecisionVariable[] FromData(int[][] inputs)
{
int cols = inputs.Columns();
var variables = new DecisionVariable[cols];
for (int i = 0; i < variables.Length; i++)
{
variables[i] = new DecisionVariable(i.ToString(), inputs.GetColumn(i).GetRange());
}
return(variables);
}
/// <summary>
/// Learns a model that can map the given inputs to the given outputs.
/// </summary>
///
/// <param name="x">The model inputs.</param>
/// <param name="y">The desired outputs associated with each <paramref name="x">inputs</paramref>.</param>
/// <param name="weights">The weight of importance for each input-output pair.</param>
///
/// <returns>A model that has learned how to produce <paramref name="y"/> given <paramref name="x"/>.</returns>
///
public RandomForest Learn(double[][] x, int[] y, double[] weights = null)
{
if (forest == null)
{
int classes = y.Max() + 1;
this.forest = new RandomForest(NumberOfTrees, classes);
if (this.attributes == null)
{
this.attributes = DecisionVariable.FromData(x);
}
for (int i = 0; i < forest.Trees.Length; i++)
{
forest.Trees[i] = new DecisionTree(attributes, classes);
}
}
run(x, y);
return(this.forest);
}
/// <summary>
/// Creates a set of decision variables from a <see cref="Codification"/> codebook.
/// </summary>
///
/// <param name="codebook">The codebook containing information about the variables.</param>
/// <param name="columns">The columns to consider as decision variables.</param>
///
/// <returns>An array of <see cref="DecisionVariable"/> objects
/// initialized with the values from the codebook.</returns>
///
public static DecisionVariable[] FromCodebook(Codification codebook, params string[] columns)
{
DecisionVariable[] variables = new DecisionVariable[columns.Length];
for (int i = 0; i < variables.Length; i++)
{
string name = columns[i];
Codification.Options col;
if (codebook.Columns.TryGetValue(name, out col))
{
variables[i] = new DecisionVariable(name, col.NumberOfSymbols);
}
else
{
variables[i] = new DecisionVariable(name, DecisionVariableKind.Continuous);
}
}
return(variables);
}
