quickModel: Quickly Creating BigML Models

Description

Quickly Creating BigML Models

Usage

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

Arguments

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.

Value

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

Details

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.

References

https://bigml.com/developers/models