ft_robust_scaler: Feature Transformation - RobustScaler (Estimator)

In sparklyr: R Interface to Apache Spark

Feature Transformation – RobustScaler (Estimator)

Description

RobustScaler removes the median and scales the data according to the quantile range. The quantile range is by default IQR (Interquartile Range, quantile range between the 1st quartile = 25th quantile and the 3rd quartile = 75th quantile) but can be configured. Centering and scaling happen independently on each feature by computing the relevant statistics on the samples in the training set. Median and quantile range are then stored to be used on later data using the transform method. Note that missing values are ignored in the computation of medians and ranges.

Usage

ft_robust_scaler(
  x,
  input_col = NULL,
  output_col = NULL,
  lower = 0.25,
  upper = 0.75,
  with_centering = TRUE,
  with_scaling = TRUE,
  relative_error = 0.001,
  uid = random_string("ft_robust_scaler_"),
  ...
)

Arguments

x	A spark_connection, ml_pipeline, or a tbl_spark.
input_col	The name of the input column.
output_col	The name of the output column.
lower	Lower quantile to calculate quantile range.
upper	Upper quantile to calculate quantile range.
with_centering	Whether to center data with median.
with_scaling	Whether to scale the data to quantile range.
relative_error	The target relative error for quantile computation.
uid	A character string used to uniquely identify the feature transformer.
...	Optional arguments; currently unused.

Details

In the case where x is a tbl_spark, the estimator fits against x to obtain a transformer, returning a tbl_spark.

Value

The object returned depends on the class of x. If it is a spark_connection, the function returns a ml_estimator or a ml_estimator object. If it is a ml_pipeline, it will return a pipeline with the transformer or estimator appended to it. If a tbl_spark, it will return a tbl_spark with the transformation applied to it.

See Also

Other feature transformers: ft_binarizer(), ft_bucketizer(), ft_chisq_selector(), ft_count_vectorizer(), ft_dct(), ft_elementwise_product(), ft_feature_hasher(), ft_hashing_tf(), ft_idf(), ft_imputer(), ft_index_to_string(), ft_interaction(), ft_lsh, ft_max_abs_scaler(), ft_min_max_scaler(), ft_ngram(), ft_normalizer(), ft_one_hot_encoder(), ft_one_hot_encoder_estimator(), ft_pca(), ft_polynomial_expansion(), ft_quantile_discretizer(), ft_r_formula(), ft_regex_tokenizer(), ft_sql_transformer(), ft_standard_scaler(), ft_stop_words_remover(), ft_string_indexer(), ft_tokenizer(), ft_vector_assembler(), ft_vector_indexer(), ft_vector_slicer(), ft_word2vec()

sparklyr documentation built on May 29, 2024, 2:58 a.m.