Trait

com.johnsnowlabs.nlp.eval.resolution

EvalEntityResolver

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trait EvalEntityResolver extends AnyRef

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  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. def accuracy(dataset: DataFrame, trueCol: String, resolverCol: String): Double

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    calculates the accuracy metric for the EntityResolverModel in the provided dataset; the dataset should contain a column with the true code and a column from the EntityResolverModel annotator

    calculates the accuracy metric for the EntityResolverModel in the provided dataset; the dataset should contain a column with the true code and a column from the EntityResolverModel annotator

    dataset

    Transformed DataFrame

    trueCol

    Column with the ground truth code

    resolverCol

    Column with the EntityResolverModel annotation

    returns

    The rate of correct entities

  5. final def asInstanceOf[T0]: T0

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  12. def hitsAtK(dataset: DataFrame, trueCol: String, resolverCol: String, k: Int, numOfChars: Int = 0): Double

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    dataset

    Transformed DataFrame

    trueCol

    Column with the ground truth code

    resolverCol

    Column with the EntityResolverModel annotation

    k

    Number of results to include in the set (k parameter for Hits@K)

    numOfChars

    Number of characters to compare from the codes starting from left; defaults to 0 which compares the full code

    returns

    The rate of correct entities appearing in the top k entries for each instance list

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