Esempio n. 1
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 /// <summary>
 /// Initializes a new instance of the FbtBuildParameters class.
 /// </summary>
 /// <param name="supportThreshold">Number of co-occurrences of items
 /// to be considered for modeling.</param>
 /// <param name="maxItemSetSize">Bound for number of items in a
 /// frequent set.</param>
 /// <param name="minimalScore">Minimal score that a frequent set
 /// should have in order to be included in the returned
 /// results.</param>
 /// <param name="similarityFunction">Defines the similarity function
 /// to be used by the build.
 /// Lift favors serendipity, Co-occurrence favors
 /// predictability, and Jaccard is a nice compromise between the
 /// two.</param>
 /// <param name="enableModelingInsights">Enable or disable metrics
 /// computation for the model.</param>
 /// <param name="splitterStrategy">Defines the splitter strategy to be
 /// used by the build.
 /// RandomSplitter splits the usage data in train and test
 /// sets based on the given
 /// randomSplitterParameters value.
 /// LastEventSplitter splits the usage data in train and
 /// test sets based on the last
 /// transaction for a each user.</param>
 /// <param name="randomSplitterParameters">Specifies the parameters to
 /// be used for random splitter.</param>
 /// <param name="dateSplitterParameters">Specifies the parameters to
 /// be used for date splitter.</param>
 /// <param name="popularItemBenchmarkWindow">Specifies the parameters
 /// to be used for computing popular items for modeling insights. (in
 /// number of days)</param>
 public FbtBuildParameters(int? supportThreshold = default(int?), int? maxItemSetSize = default(int?), double? minimalScore = default(double?), string similarityFunction = default(string), bool? enableModelingInsights = default(bool?), string splitterStrategy = default(string), RandomSplitterParameters randomSplitterParameters = default(RandomSplitterParameters), DateSplitterParameters dateSplitterParameters = default(DateSplitterParameters), int? popularItemBenchmarkWindow = default(int?))
 {
     SupportThreshold = supportThreshold;
     MaxItemSetSize = maxItemSetSize;
     MinimalScore = minimalScore;
     SimilarityFunction = similarityFunction;
     EnableModelingInsights = enableModelingInsights;
     SplitterStrategy = splitterStrategy;
     RandomSplitterParameters = randomSplitterParameters;
     DateSplitterParameters = dateSplitterParameters;
     PopularItemBenchmarkWindow = popularItemBenchmarkWindow;
 }
 /// <summary>
 /// Initializes a new instance of the RecommendationBuildParameters
 /// class.
 /// </summary>
 /// <param name="numberOfModelIterations">The number of iterations the
 /// model performs.
 /// The higher the number, the better accuracy, but
 /// compute time will be higher.</param>
 /// <param name="numberOfModelDimensions">The number of dimensions
 /// relates to the number of 'features' the model will try to find
 /// within your data.
 /// Increasing the number of dimensions will allow better
 /// fine-tuning of the results into smaller clusters.
 /// However, too many dimensions will prevent the model
 /// from finding correlations between items.</param>
 /// <param name="itemCutOffLowerBound">Defines the item lower bound
 /// for usage condenser.</param>
 /// <param name="itemCutOffUpperBound">Defines the item upper bound
 /// for usage condenser.</param>
 /// <param name="userCutOffLowerBound">Defines the user lower bound
 /// for usage condenser.</param>
 /// <param name="userCutOffUpperBound">Defines the user upper bound
 /// for usage condenser.</param>
 /// <param name="enableModelingInsights">Enable or disable metrics
 /// computation for the model.</param>
 /// <param name="splitterStrategy">Defines the splitter strategy to be
 /// used by the build.
 /// RandomSplitter splits the usage data in train and test
 /// sets based on the given
 /// randomSplitterParameters value.
 /// LastEventSplitter splits the usage data in train and
 /// test sets based on the last
 /// transaction for a each user.</param>
 /// <param name="randomSplitterParameters">Specifies the parameters to
 /// be used for random splitter.</param>
 /// <param name="dateSplitterParameters">Specifies the parameters to
 /// be used for date splitter.</param>
 /// <param name="popularItemBenchmarkWindow">Specifies the parameters
 /// to be used for computing popular items for modeling insights. (in
 /// number of days)</param>
 /// <param name="useFeaturesInModel">Indicates if features can be used
 /// in order to enhance the recommendation model.</param>
 /// <param name="modelingFeatureList">Comma-separated list of feature
 /// names to be used during build.</param>
 /// <param name="allowColdItemPlacement">Indicates if the
 /// recommendation should also push cold items via feature
 /// similarity.</param>
 /// <param name="enableFeatureCorrelation">Indicates if features can
 /// be used in reasoning.</param>
 /// <param name="reasoningFeatureList">Comma-separated list of feature
 /// names to be used for reasoning sentences (e.g. recommendation
 /// explanations).</param>
 /// <param name="enableU2I">Allow the personalized recommendation
 /// a.k.a. U2I (user to item recommendations).</param>
 public RecommendationBuildParameters(int? numberOfModelIterations = default(int?), int? numberOfModelDimensions = default(int?), int? itemCutOffLowerBound = default(int?), int? itemCutOffUpperBound = default(int?), int? userCutOffLowerBound = default(int?), int? userCutOffUpperBound = default(int?), bool? enableModelingInsights = default(bool?), string splitterStrategy = default(string), RandomSplitterParameters randomSplitterParameters = default(RandomSplitterParameters), DateSplitterParameters dateSplitterParameters = default(DateSplitterParameters), int? popularItemBenchmarkWindow = default(int?), bool? useFeaturesInModel = default(bool?), string modelingFeatureList = default(string), bool? allowColdItemPlacement = default(bool?), bool? enableFeatureCorrelation = default(bool?), string reasoningFeatureList = default(string), bool? enableU2I = default(bool?))
 {
     NumberOfModelIterations = numberOfModelIterations;
     NumberOfModelDimensions = numberOfModelDimensions;
     ItemCutOffLowerBound = itemCutOffLowerBound;
     ItemCutOffUpperBound = itemCutOffUpperBound;
     UserCutOffLowerBound = userCutOffLowerBound;
     UserCutOffUpperBound = userCutOffUpperBound;
     EnableModelingInsights = enableModelingInsights;
     SplitterStrategy = splitterStrategy;
     RandomSplitterParameters = randomSplitterParameters;
     DateSplitterParameters = dateSplitterParameters;
     PopularItemBenchmarkWindow = popularItemBenchmarkWindow;
     UseFeaturesInModel = useFeaturesInModel;
     ModelingFeatureList = modelingFeatureList;
     AllowColdItemPlacement = allowColdItemPlacement;
     EnableFeatureCorrelation = enableFeatureCorrelation;
     ReasoningFeatureList = reasoningFeatureList;
     EnableU2I = enableU2I;
 }