`QuantileDiscretizer` takes a column with continuous features and outputs a column with binned
categorical features. The number of bins can be set using the `numBuckets` parameter.
The bin ranges are chosen using an approximate algorithm (see the documentation for
[[org.apache.spark.sql.DatasetStatFunctions.approxQuantile approxQuantile]]
for a detailed description). The precision of the approximation can be controlled with the
`relativeError` parameter. The lower and upper bin bounds will be `-Infinity` and `+Infinity`,
covering all real values.
Constructor
new QuantileDiscretizer(uidopt)
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Extends
Methods
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module:eclairjs/ml/feature.QuantileDiscretizer
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module:eclairjs/ml/feature.QuantileDiscretizer
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module:eclairjs/ml/param.ParamMap
fit(dataset) → {Bucketizer}
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Bucketizer
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module:eclairjs/ml/feature.QuantileDiscretizer
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number
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module:eclairjs/ml/feature.QuantileDiscretizer
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module:eclairjs/ml/feature.QuantileDiscretizer
setRelativeError(value) → {type}
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