ml-model-constructors

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Constructors for `ml_model` Objects

Functions for developers writing extensions for Spark ML. These functions are constructors for `ml_model` objects that are returned when using the formula interface.

Keywords
internal
Usage
new_ml_model_prediction(pipeline_model, formula, dataset, label_col,
  features_col, ..., class = character())

new_ml_model(pipeline_model, formula, dataset, ..., class = character())

new_ml_model_classification(pipeline_model, formula, dataset, label_col, features_col, predicted_label_col, ..., class = character())

new_ml_model_regression(pipeline_model, formula, dataset, label_col, features_col, ..., class = character())

new_ml_model_clustering(pipeline_model, formula, dataset, features_col, ..., class = character())

ml_supervised_pipeline(predictor, dataset, formula, features_col, label_col)

ml_clustering_pipeline(predictor, dataset, formula, features_col)

ml_construct_model_supervised(constructor, predictor, formula, dataset, features_col, label_col, ...)

ml_construct_model_clustering(constructor, predictor, formula, dataset, features_col, ...)

Arguments
pipeline_model

The pipeline model object returned by `ml_supervised_pipeline()`.

formula

The formula used for data preprocessing

dataset

The training dataset.

label_col

Label column name. The column should be a numeric column. Usually this column is output by ft_r_formula.

features_col

Features column name, as a length-one character vector. The column should be single vector column of numeric values. Usually this column is output by ft_r_formula.

class

Name of the subclass.

predictor

The pipeline stage corresponding to the ML algorithm.

constructor

The constructor function for the `ml_model`.

Aliases
  • ml-model-constructors
  • new_ml_model_prediction
  • new_ml_model
  • new_ml_model_classification
  • new_ml_model_regression
  • new_ml_model_clustering
  • ml_supervised_pipeline
  • ml_clustering_pipeline
  • ml_construct_model_supervised
  • ml_construct_model_clustering
Documentation reproduced from package sparklyr, version 1.0.4, License: Apache License 2.0 | file LICENSE

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