/// <summary>
/// Trains a model using SAR.
/// </summary>
/// <param name="settings">The training settings</param>
/// <param name="usageEvents">The usage events to use for training</param>
/// <param name="catalogItems">The catalog items to use for training</param>
/// <param name="uniqueUsersCount">The number of users in the user id index file.</param>
/// <param name="uniqueUsageItemsCount">The number of usage items in the item id index file</param>
/// <param name="cancellationToken">A cancellation token</param>
public IPredictorModel Train(ITrainingSettings settings,
IList <SarUsageEvent> usageEvents,
IList <SarCatalogItem> catalogItems,
int uniqueUsersCount,
int uniqueUsageItemsCount,
CancellationToken cancellationToken)
{
if (settings == null)
{
throw new ArgumentNullException(nameof(settings));
}
if (usageEvents == null)
{
throw new ArgumentNullException(nameof(usageEvents));
}
if (settings.EnableColdItemPlacement && catalogItems == null)
{
throw new ArgumentNullException(nameof(catalogItems));
}
if (uniqueUsersCount < 0)
{
var exception = new ArgumentException($"{nameof(uniqueUsersCount)} must be a positive integer");
_tracer.TraceWarning(exception.ToString());
throw exception;
}
if (uniqueUsageItemsCount < 0)
{
var exception = new ArgumentException($"{nameof(uniqueUsageItemsCount)} must be a positive integer");
_tracer.TraceWarning(exception.ToString());
throw exception;
}
cancellationToken.ThrowIfCancellationRequested();
using (TlcEnvironment environment = new TlcEnvironment(verbose: true))
{
_detectedFeatureWeights = null;
try
{
environment.AddListener <ChannelMessage>(ChannelMessageListener);
IHost environmentHost = environment.Register("SarHost");
// bind the cancellation token to SAR cancellation
using (cancellationToken.Register(() => { environmentHost.StopExecution(); }))
{
_tracer.TraceInformation("Starting training model using SAR");
return(TrainModel(environmentHost, settings, usageEvents, catalogItems, uniqueUsersCount,
uniqueUsageItemsCount));
}
}
finally
{
environment.RemoveListener <ChannelMessage>(ChannelMessageListener);
}
}
}
/// <summary>
/// Trains a model using SAR.
/// </summary>
/// <param name="settings">The training settings</param>
/// <param name="usageEvents">The usage events to use for training</param>
/// <param name="catalogItems">The catalog items to use for training</param>
/// <param name="featureNames">The names of the catalog items features, in the same order as the feature values in the catalog</param>
/// <param name="uniqueUsersCount">The number of users in the user id index file.</param>
/// <param name="uniqueUsageItemsCount">The number of usage items in the item id index file</param>
/// <param name="catalogFeatureWeights">The computed catalog items features weights (if relevant)</param>
/// <param name="cancellationToken">A cancellation token</param>
public IPredictorModel Train(ITrainingSettings settings,
IList <SarUsageEvent> usageEvents,
IList <SarCatalogItem> catalogItems,
string[] featureNames,
int uniqueUsersCount,
int uniqueUsageItemsCount,
out IDictionary <string, double> catalogFeatureWeights,
CancellationToken cancellationToken)
{
if (settings == null)
{
throw new ArgumentNullException(nameof(settings));
}
if (usageEvents == null)
{
throw new ArgumentNullException(nameof(usageEvents));
}
if (settings.EnableColdItemPlacement && catalogItems == null)
{
throw new ArgumentNullException(nameof(catalogItems));
}
if (uniqueUsersCount < 0)
{
var exception = new ArgumentException($"{nameof(uniqueUsersCount)} must be a positive integer");
_tracer.TraceWarning(exception.ToString());
throw exception;
}
if (uniqueUsageItemsCount < 0)
{
var exception = new ArgumentException($"{nameof(uniqueUsageItemsCount)} must be a positive integer");
_tracer.TraceWarning(exception.ToString());
throw exception;
}
cancellationToken.ThrowIfCancellationRequested();
using (TlcEnvironment environment = new TlcEnvironment(verbose: true))
{
_detectedFeatureWeights = null;
try
{
environment.AddListener <ChannelMessage>(ChannelMessageListener);
IHost environmentHost = environment.Register("SarHost");
// bind the cancellation token to SAR cancellation
using (cancellationToken.Register(() => { environmentHost.StopExecution(); }))
{
_tracer.TraceInformation("Starting training model using SAR");
IPredictorModel model = TrainModel(environmentHost, settings, usageEvents, catalogItems, uniqueUsersCount,
uniqueUsageItemsCount);
catalogFeatureWeights = new Dictionary <string, double>();
if (_detectedFeatureWeights != null && featureNames != null)
{
if (_detectedFeatureWeights.Length == featureNames.Length)
{
for (int i = 0; i < featureNames.Length; i++)
{
catalogFeatureWeights[featureNames[i]] = _detectedFeatureWeights[i];
}
}
else
{
_tracer.TraceWarning(
$"Found a mismatch between number of feature names ({featureNames.Length}) and the number of feature weights ({_detectedFeatureWeights.Length})");
}
}
return(model);
}
}
finally
{
environment.RemoveListener <ChannelMessage>(ChannelMessageListener);
}
}
}
