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KNearestNeighborsImputer

The KNearestNeighborsImputer replaces missing values in given Columns with the mean value of the K-nearest neighbors.

Parent type: TableTransformer

Parameters:

Name Type Description Default
neighborCount Int The number of neighbors to consider when imputing missing values. -
selector union<List<String>, String?> The list of columns used to impute missing values. If 'None', all columns are used. null
valueToReplace union<Float, String?> The placeholder for the missing values. All occurrences ofmissing_values will be imputed. null
Stub code in KNearestNeighborsImputer.sdsstub 

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class KNearestNeighborsImputer(
    @PythonName("neighbor_count") neighborCount: Int,
    selector: union<List<String>, String, Nothing?> = null,
    @PythonName("value_to_replace") valueToReplace: union<Float, String, Nothing?> = null
) sub TableTransformer {
    /**
     * The number of neighbors to consider when imputing missing values.
     */
    @PythonName("neighbor_count") attr neighborCount: Int
    /**
     * The value to replace.
     */
    @PythonName("value_to_replace") attr valueToReplace: Any?

    /**
     * Learn a transformation for a set of columns in a table.
     *
     * **Note:** This transformer is not modified.
     *
     * @param table The table used to fit the transformer.
     *
     * @result fittedTransformer The fitted transformer.
     */
    @Pure
    @Category(DataScienceCategory.DataProcessingQTransformer)
    fun fit(
        table: Table
    ) -> fittedTransformer: KNearestNeighborsImputer

    /**
     * Learn a transformation for a set of columns in a table and apply the learned transformation to the same table.
     *
     * **Note:** Neither this transformer nor the given table are modified.
     *
     * @param table The table used to fit the transformer. The transformer is then applied to this table.
     *
     * @result fittedTransformer The fitted transformer.
     * @result transformedTable The transformed table.
     */
    @Pure
    @PythonName("fit_and_transform")
    @Category(DataScienceCategory.DataProcessingQTransformer)
    fun fitAndTransform(
        table: Table
    ) -> (fittedTransformer: KNearestNeighborsImputer, transformedTable: Table)
}

isFitted

Whether the transformer is fitted.

Type: Boolean

neighborCount

The number of neighbors to consider when imputing missing values.

Type: Int

valueToReplace

The value to replace.

Type: Any?

fit

Learn a transformation for a set of columns in a table.

Note: This transformer is not modified.

Parameters:

Name Type Description Default
table Table The table used to fit the transformer. -

Results:

Name Type Description
fittedTransformer KNearestNeighborsImputer The fitted transformer.
Stub code in KNearestNeighborsImputer.sdsstub 

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@Pure
@Category(DataScienceCategory.DataProcessingQTransformer)
fun fit(
    table: Table
) -> fittedTransformer: KNearestNeighborsImputer

fitAndTransform

Learn a transformation for a set of columns in a table and apply the learned transformation to the same table.

Note: Neither this transformer nor the given table are modified.

Parameters:

Name Type Description Default
table Table The table used to fit the transformer. The transformer is then applied to this table. -

Results:

Name Type Description
fittedTransformer KNearestNeighborsImputer The fitted transformer.
transformedTable Table The transformed table.
Stub code in KNearestNeighborsImputer.sdsstub 

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@Pure
@PythonName("fit_and_transform")
@Category(DataScienceCategory.DataProcessingQTransformer)
fun fitAndTransform(
    table: Table
) -> (fittedTransformer: KNearestNeighborsImputer, transformedTable: Table)

transform

Apply the learned transformation to a table.

Note: The given table is not modified.

Parameters:

Name Type Description Default
table Table The table to which the learned transformation is applied. -

Results:

Name Type Description
transformedTable Table The transformed table.
Stub code in TableTransformer.sdsstub 

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@Pure
fun transform(
    table: Table
) -> transformedTable: Table