| 프로퍼티 | 타입 | 설명 |
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| 메소드 | 설명 | |
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| RecommendationBuildParameters ( ) : System.Linq |
Initializes a new instance of the RecommendationBuildParameters class.
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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), |
Initializes a new instance of the RecommendationBuildParameters class.
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| public RecommendationBuildParameters ( ) : System.Linq | ||
| 리턴 | System.Linq | |
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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), |
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| numberOfModelIterations | int | The number of iterations the /// model performs. /// The higher the number, the better accuracy, but /// compute time will be higher. |
| numberOfModelDimensions | int | 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. |
| itemCutOffLowerBound | int | Defines the item lower bound /// for usage condenser. |
| itemCutOffUpperBound | int | Defines the item upper bound /// for usage condenser. |
| userCutOffLowerBound | int | Defines the user lower bound /// for usage condenser. |
| userCutOffUpperBound | int | Defines the user upper bound /// for usage condenser. |
| enableModelingInsights | bool | Enable or disable metrics /// computation for the model. |
| splitterStrategy | string | 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. |
| randomSplitterParameters | RandomSplitterParameters | Specifies the parameters to /// be used for random splitter. |
| dateSplitterParameters | Specifies the parameters to /// be used for date splitter. | |
| popularItemBenchmarkWindow | int | Specifies the parameters /// to be used for computing popular items for modeling insights. (in /// number of days) |
| useFeaturesInModel | bool | Indicates if features can be used /// in order to enhance the recommendation model. |
| modelingFeatureList | string | Comma-separated list of feature /// names to be used during build. |
| allowColdItemPlacement | bool | Indicates if the /// recommendation should also push cold items via feature /// similarity. |
| enableFeatureCorrelation | bool | Indicates if features can /// be used in reasoning. |
| reasoningFeatureList | string | Comma-separated list of feature /// names to be used for reasoning sentences (e.g. recommendation /// explanations). |
| enableU2I | bool | Allow the personalized recommendation /// a.k.a. U2I (user to item recommendations). |
| 리턴 | System.Linq | |