rminer: Interfaces for rminer package for data science pipelines.

In rbertolusso/intubate: Interface to Popular R Functions for Data Science Pipelines

Description

Interfaces to rminer functions that can be used in a pipeline implemented by magrittr.

Usage

ntbt_fit(data, ...)
ntbt_mining(data, ...)

Arguments

data	data frame, tibble, list, ...
...	Other arguments passed to the corresponding interfaced function.

Details

Interfaces call their corresponding interfaced function.

Value

Object returned by interfaced function.

Author(s)

Roberto Bertolusso

Examples

## Not run: 
library(intubate)
library(magrittr)
library(rminer)

## ntbt_fit: Fit a supervised data mining model (classification or regression) model
x1 <- rnorm(200,100,20)
x2 <- rnorm(200,100,20)
y <- 0.7*sin(x1/(25*pi))+0.3*sin(x2/(25*pi))
dta <- data.frame(x1, x2, y)

## Original function to interface
fit(y ~ x1 + x2, data = dta, model = "mlpe")

## The interface puts data as first parameter
ntbt_fit(dta, y ~ x1 + x2, model = "mlpe")

## so it can be used easily in a pipeline.
dta %>%
  ntbt_fit(y ~ x1 + x2, model = "mlpe")


## ntbt_mining: Powerful function that trains and tests a particular fit model
##              under several runs and a given validation method
## Original function to interface
mining(y ~ x1 + x2, data = dta, model = "mlpe")

## The interface puts data as first parameter
ntbt_mining(dta, y ~ x1 + x2, model = "mlpe")

## so it can be used easily in a pipeline.
dta %>%
  ntbt_mining(y ~ x1 + x2, model = "mlpe")

## End(Not run)

rbertolusso/intubate documentation built on May 27, 2019, 3 a.m.