quickModel: Quickly Creating BigML Models
In bigml: Bindings for the BigML API

Description Usage Arguments Details Value Author(s) References See Also

Quickly Creating BigML Models

quickModel(data, input_fields = names(data),
  objective_fields = tail(names(data), n = 1),
  name = paste(deparse(substitute(data)), "'s model", sep = ""),
  range = NULL, ...)

`data`	A matrix or data frame containing data to upload to bigml.
`input_fields`	A vector of string names to use for training.
`objective_fields`	A single string value to use as an objective field (objective_fields is plural for future use).
`name`	A string giving the name of the model.
`range`	A two element numeric vector that defines a range over the dataset in which to train on.
`...`	Arbitrary named arguments that are passed on to `formEncodeURL` in order to create form-encoded URL options.

quickModel will take its "data" dataframe argument and attempt to create a dataset using quickDataset. It is possible to specify the input_fields and objective_fields using the simple names from the data argument.

`category`	numeric
`code`	numeric
`columns`	numeric
`created`	character
`credits`	numeric
`dataset`	character
`dataset_status`	logical
`description`	character
`input_fields`	character
`locale`	character
`max_columns`	numeric
`max_rows`	numeric
`model`	list
`name`	character
`number_of_predictions`	numeric
`objective_fields`	character
`private`	logical
`range`	numeric
`resource`	character
`rows`	numeric
`size`	numeric
`source`	character
`source_status`	logical
`status`	list
`tags`	AsIs
`updated`	character