/// <summary> /// Creates a <see cref="SupportVectorMachine"/> from the specified file. /// </summary> /// <param name="fileName">A string that contains the name of the file from which to create the <see cref="SupportVectorMachine"/>.</param> /// <returns>The <see cref="SupportVectorMachine"/> this method creates.</returns> public static SupportVectorMachine FromFile(string fileName) => SupportVectorMachine.FromString(File.ReadAllText(fileName, Encoding.UTF8));
/// <summary> /// Creates a <see cref="SupportVectorMachine"/> from the specified byte array. /// </summary> /// <param name="buffer">The buffer to read the <see cref="SupportVectorMachine"/> from.</param> /// <returns>The <see cref="SupportVectorMachine"/> this method creates.</returns> public static SupportVectorMachine FromMemory(byte[] buffer) => SupportVectorMachine.FromString(UTF8Encoding.UTF8.GetString(buffer));
/// <summary>
/// Learns a model that can map the given inputs to the given outputs.
/// </summary>
/// <param name="trainer">The learning algorithm.</param>
/// <param name="numberOfClasses">The number of classes.</param>
/// <param name="x">The input vectors <paramref name="x"/>.</param>
/// <param name="y">The expected binary output <paramref name="y"/>.</param>
/// <param name="weights">The <c>weight</c> of importance for each input vector (if supported by the learning algorithm).</param>
/// <param name="cancellationToken">The cancellationToken token used to notify the machine that the operation should be canceled.</param>
/// <exception cref="ArgumentNullException">
/// <para><paramref name="trainer"/> is <b>null</b>.</para>
/// <para>-or-</para>
/// <para><paramref name="x"/> is <b>null</b>.</para>
/// <para>-or-</para>
/// <para><paramref name="y"/> is <b>null</b>.</para>
/// </exception>
/// <exception cref="ArgumentException">
/// <para><paramref name="numberOfClasses"/> is less than 2.</para>
/// <para>-or-</para>
/// <para>The number of elements in <paramref name="y"/> does not match the number of elements in <paramref name="x"/>.</para>
/// <para>-or-</para>
/// <para><paramref name="weights"/> is not <b>null</b> and the number of elements in <paramref name="weights"/> does not match the number of elements in <paramref name="x"/>.</para>
/// </exception>
/// <returns>
/// The <see cref="OneVsAllSupportVectorMachine"/> learned by this method.
/// A model that has learned how to produce <paramref name="y"/> given <paramref name="x"/>.
/// </returns>
public static OneVsAllSupportVectorMachine Learn(
ISupportVectorMachineLearning trainer,
int numberOfClasses,
IList <float[]> x,
IList <int> y,
IList <float> weights,
CancellationToken cancellationToken)
{
if (trainer == null)
{
throw new ArgumentNullException(nameof(trainer));
}
if (x == null)
{
throw new ArgumentNullException(nameof(x));
}
if (y == null)
{
throw new ArgumentNullException(nameof(y));
}
if (numberOfClasses < 2)
{
throw new ArgumentException("The machine must have at least two classes.", nameof(numberOfClasses));
}
if (y.Count != x.Count)
{
throw new ArgumentException("The number of output labels must match the number of input vectors.", nameof(y));
}
// create the machines
SupportVectorMachine[] machines = new SupportVectorMachine[numberOfClasses];
// train each machine
int sampleCount = x.Count;
CommonParallel.For(
0,
machines.Length,
(a, b) =>
{
for (int i = a; i < b; i++)
{
bool[] expected = new bool[sampleCount];
for (int j = 0; j < sampleCount; j++)
{
expected[j] = y[j] == i;
}
machines[i] = SupportVectorMachine.Learn(trainer, x, expected, weights, cancellationToken);
}
},
new ParallelOptions()
{
CancellationToken = cancellationToken,
});
return(new OneVsAllSupportVectorMachine(machines));
}
