/// <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;
}