private void PredictForCFModel(MLEntityPredictor predictor)
{
var modelLoader = ClassFactory.Get <IMLModelLoader>();
if (!modelLoader.TryLoadModelForPrediction(UserConnection, MLModelId, out MLModelConfig modelConfig))
{
throw new InvalidObjectStateException($"Recommendation model with id {MLModelId} was not found"
+ " or not ready for making predictions.");
}
if (modelConfig.CFResultSchemaUId.IsEmpty())
{
throw new NotImplementedException($"Model {MLModelId} is not configured for saving results");
}
EntitySchema modelRootSchema = UserConnection.EntitySchemaManager
.GetInstanceByUId(modelConfig.EntitySchemaId);
EntitySchemaQuery usersEsq = GetCFSchemaDataEsq(modelRootSchema,
modelConfig.CFUserColumnPath, CFUserFilterData);
IEnumerable <Guid> users = ReadCFData(usersEsq);
EntitySchemaQuery itemsEsq = GetCFSchemaDataEsq(modelRootSchema, modelConfig.CFItemColumnPath,
CFItemFilterData);
bool isItemsFilterEmpty = itemsEsq.Filters.IsEmpty();
IEnumerable <Guid> items = isItemsFilterEmpty ? Enumerable.Empty <Guid>() : ReadCFData(itemsEsq);
RecommendationFilterItemsMode filterItemsMode = isItemsFilterEmpty
? RecommendationFilterItemsMode.Black
: RecommendationFilterItemsMode.White;
predictor.Recommend(MLModelId, users.ToList(), CFTopN, items.ToList(),
filterItemsMode: filterItemsMode, filterAlreadyInteractedItems: CFFilterAlreadyInteractedItems);
}
/// <summary>
/// Performs recommendation for specified users.
/// </summary>
/// <param name="model">Model instance.</param>
/// <param name="users">Users to get recommendation.</param>
/// <param name="recordsCount">Number of items to recommend for each user.</param>
/// <param name="filterItems">Items to filter.</param>
/// <param name="filterItemsMode">Mode of filter,</param>
/// <param name="filterAlreadyInteractedItems">Filter out already interacted items from prediction.</param>
/// <param name="userItems">Updated users items.</param>
/// <param name="recalculateUsers">Recalculate users recommendations using <see cref="userItems"/></param>
public RecommendationResponse Recommend(MLModelConfig model, List <Guid> users, int recordsCount = 10,
List <Guid> filterItems = null,
RecommendationFilterItemsMode filterItemsMode = RecommendationFilterItemsMode.White,
bool filterAlreadyInteractedItems = true, List <DatasetValue> userItems = null,
bool recalculateUsers = false)
{
RecommendationRequest request = new RecommendationRequest {
ModelId = model.ModelInstanceUId,
PredictionParams = new RecommendationInput {
UserIds = users.Select(e => e.ToString()).ToList(),
PredictionRecordsCount = recordsCount,
FilterItems = filterItems?.Select(e => e.ToString()).ToList() ?? new List <string>(),
FilterItemsMode = filterItemsMode.ToString().ToLowerInvariant(),
FilterAlreadyInteractedItems = filterAlreadyInteractedItems,
UserItems = userItems,
RecalculateUsers = recalculateUsers
}
};
return(Post <RecommendationResponse>(model.PredictionEndpoint, request, RecommendationTimeoutSec));
}
