/// <summary>
/// Initializes a new Optimizer using the default values.
/// <param name="theta">Theta to optimize.</param>
/// <param name="maxIterations">Maximum number of iterations.</param>
/// <param name="learningRate">Learning Rate (alpha) (Optional).</param>
/// <param name="momentum">Momentum parameter for use in accelerated methods (Optional).</param>
/// <param name="optimizationMethod">Type of optimization method to use (Optional).</param>
/// <param name="optimizer">An external typed optimization method to use (Optional).</param>
/// </summary>
public Optimizer(Vector theta, int maxIterations, double learningRate = 1.0, double momentum = 0.9,
OptimizationMethods optimizationMethod = OptimizationMethods.StochasticGradientDescent, OptimizationMethod optimizer = null)
{
this.Completed = false;
if (optimizationMethod != OptimizationMethods.External)
{
switch (optimizationMethod)
{
case OptimizationMethods.FastGradientDescent: optimizer = new numl.Math.Optimization.Methods.GradientDescent.FastGradientDescent() { Momentum = momentum }; break;
case OptimizationMethods.StochasticGradientDescent: optimizer = new numl.Math.Optimization.Methods.GradientDescent.StochasticGradientDescent(); break;
case OptimizationMethods.NAGDescent: optimizer = new numl.Math.Optimization.Methods.GradientDescent.NAGDescent() { Momentum = momentum }; break;
}
}
this.OpimizationMethod = optimizer;
this.Properties = new OptimizerProperties()
{
Iteration = 0,
MaxIterations = maxIterations,
Cost = double.MaxValue,
Gradient = Vector.Zeros(theta.Length),
Theta = theta,
LearningRate = learningRate,
Momentum = momentum
};
}
/// <summary>
/// Initializes a new Optimizer using the default values.
/// <param name="theta">Theta to optimize.</param>
/// <param name="maxIterations">Maximum number of iterations.</param>
/// <param name="learningRate">Learning Rate (alpha) (Optional).</param>
/// <param name="momentum">Momentum parameter for use in accelerated methods (Optional).</param>
/// <param name="optimizationMethod">Type of optimization method to use (Optional).</param>
/// <param name="optimizer">An external typed optimization method to use (Optional).</param>
/// </summary>
public Optimizer(Vector theta, int maxIterations, double learningRate = 1.0, double momentum = 0.9,
OptimizationMethods optimizationMethod = OptimizationMethods.StochasticGradientDescent, OptimizationMethod optimizer = null)
{
this.Completed = false;
if (optimizationMethod != OptimizationMethods.External)
{
switch (optimizationMethod)
{
case OptimizationMethods.FastGradientDescent: optimizer = new FastGradientDescent()
{
Momentum = momentum
}; break;
case OptimizationMethods.StochasticGradientDescent: optimizer = new StochasticGradientDescent(); break;
case OptimizationMethods.NAGDescent: optimizer = new NAGDescent()
{
Momentum = momentum
}; break;
}
}
this.OpimizationMethod = optimizer;
this.Properties = new OptimizerProperties()
{
Iteration = 0,
MaxIterations = maxIterations,
Cost = double.MaxValue,
Gradient = Vector.Zeros(theta.Length),
Theta = theta,
LearningRate = learningRate,
Momentum = momentum
};
}
