public AutoRegression(MLContext mlContext, AlgorithmManagerFactory factory, ModelSaver modelSaver)
{
_mlContext = mlContext;
_modelSaver = modelSaver;
_factory = factory;
LoadModels();
}
public ModelSaverTests()
{
var mlContext = new MLContext(0);
_fileSystem = new MockFileSystem();
_outputDir = _fileSystem.Path.GetTempPath();
IConfigurationBuilder configurationBuilder = new ConfigurationBuilder();
configurationBuilder.AddInMemoryCollection(new[]
{
new KeyValuePair <string, string>(ModelSaver.KEY_MODEL_SAVE_PATH, _fileSystem.Path.GetTempPath())
});
_modelSaver = new ModelSaver(mlContext, configurationBuilder.Build(), _fileSystem);
}
protected override void Process()
{
if (IterationFlag)
{
if (SaveModel)
{
ModelSaver.Pushback(Model.Clone());
ModelSaver.Request.Set();
}
switch (State)
{
case FlagState.Initial:
State = FlagState.Adjustment;
break;
case FlagState.Adjustment:
State = FlagState.Update;
{
Model.UpdateState(true);
}
break;
case FlagState.Update:
break;
default:
break;
}
}
Model.Learning(Input, Teacher, IterationFlag);
var result = Model.ShowResult(640, 480);
var process = Model.ShowProcess(0.5);
Components.Imaging.View.Show(result, "result");
Components.Imaging.View.Show(process, "process");
var span = (DateTime.Now - StartTime);
Console.WriteLine(Model.Epoch + " / " + Model.Generation + " / " + Model.OutputLayer.Variable.Error[0] +
" :" + span.Days + ":" + span.Hours + ":" + span.Minutes + ":" + span.Seconds + "'" + span.Milliseconds);
}
protected SvdTrainerBase()
{
ModelSaver = new ModelSaver();
ModelSaver.ModelPartSavers.Add(new SvdModelPartSaver());
}
public AutoMLRecommender(MLContext mlContext, AlgorithmManagerFactory factory, ModelSaver modelSaver)
{
_regression = new AutoRegression(mlContext, factory, modelSaver);
}
public IEnumerable <LearningResult> TrainModel(MLContext mlContext,
ModelSaver modelSaver,
IEnumerable <(Person, Computer)> personComputerPairs,
