public void Train(IWebApplication webApplication, IMLModel mlModel)
{
foreach (string watcher in this.Watchers)
{
Core.UIMatrix.AddElement(webApplication, watcher);
}
foreach (ModelDefinitionState validModel in this.Valid)
{
var validation = validModel.RunValidation(webApplication, mlModel,
this, validModel, true);
#if TRACE
Console.WriteLine($"Validation matrix: {validation}");
#endif
}
foreach (ModelDefinitionState validModel in this.Invalid)
{
var validation = validModel.RunValidation(webApplication, mlModel,
this, validModel, false);
#if TRACE
Console.WriteLine($"Validation matrix: {validation}");
#endif
}
}
public void ValidateAllAttributesInIMLModels(IMLModel model)
{
Assert.True(Validator.TryValidateObject(model,
new ValidationContext(model),
null, true)
, $"IMLModel {model.GetType()} is not validate");
}
public Engine(ILogger <Engine> logger, IPipeline pipeline, IMLModel mlModel, IAFINN afinn)
{
mainPredictor = mlModel;
secondOpinionPredictor = afinn;
_logger = logger;
_pipeline = pipeline;
}
/// <summary>
/// Run 'valid' and 'invalid' validations.
/// </summary>
/// <param name="webApplication">Web application handler.</param>
/// <param name="mlModel">ML model context.</param>
/// <param name="modelDefiner">Model definer context.</param>
/// <param name="validModel">Valid or invalid model context.</param>
/// <param name="valid">Validity.</param>
/// <returns>Matrix.</returns>
public IList <double> RunValidation(IWebApplication webApplication, IMLModel mlModel, IModelDefinition modelDefiner, IModelDefinitionState validModel, bool valid)
{
Core.UIMatrix.Init(webApplication);
foreach (string watcher in modelDefiner.Watchers)
{
Core.UIMatrix.AddElement(webApplication, watcher);
}
foreach (ModelDefinitionAction action in validModel.Actions)
{
switch (action.Action)
{
case "SetValue":
Application.DOM.IDomElement genericElement =
new GenericElement(webApplication.Driver)
{
Name = action.Selector
};
(genericElement as GenericElement).SetValue(action.Value?.ToString());
break;
}
}
IList <double> matrix =
Core.UIMatrix.CalculateMatrices(webApplication);
mlModel.WriteDataToCsv(csvFilePath: "Data/modelData.csv",
features: matrix, validity: valid);
webApplication.Driver.Navigate().GoToUrl(webApplication.Url);
return(matrix);
}
/// <summary>
/// Run Bayes Point Machine.
/// </summary>
/// <param name="mlModel">Machine learning model context.</param>
/// <param name="y">Y feature.</param>
/// <param name="w">Features vector.</param>
public static void Run(IMLModel mlModel, VariableArray <bool> y, Variable <Vector> w)
{
// Get Y feature range.
Range j = y.Range.Named("metal");
// Vector data of incomes length.
Vector[] xdata = new Vector[mlModel.Data.Count()];
// Vector data.
xdata = (from dblArr in (from data in mlModel.Data
select(from d in data select d))
select Vector.FromList(dblArr.ToList())).ToArray();
// Create observed variable based on xdata with validity range.
VariableArray <Vector> obs = Variable.Observed(xdata, j).Named("obs");
// Create noise.
double noise = mlModel.Noise;
y[j] = Variable.GaussianFromMeanAndVariance(Variable.InnerProduct(w, obs[j]).Named("innerProduct"), noise) > 0;
}
