README.md

In craiggrabowski/predictr: Objects For Fast Predictions Of Common Model Types

predictr

The goal of predictr is to allow for model predictions which minimize memory usage and computing time. This package provides a new type of object and adaptors for various common model types.

Installation

You can install predictr from github with:

# install.packages("devtools")
devtools::install_github("craiggrabowski/predictr")

Example

This is a basic example which illustrates predictor(), the main method defined in this package:

## basic example code
v <- seq(1024)
df <- data.frame(x = v, y = v + 1)
model <- lm(y ~ x, df)
x <- predictor(model)
predict(x, data.frame(x = c(2, 3)))
#>      [,1]
#> [1,]    3
#> [2,]    4

We create a model object using linear regression and then convert to a new object using predictor(). This new object implements the predict() method, but its implementation does not produce the same results as the original regression object. In particular, the output is now expressed as a matrix instead of a numeric vector.

The new object created by predictor() has a few advantages over the object produced using a call to lm(). First, the new object is significantly smaller than the existing model object:

pryr::object_size(model)
#> 134 kB
pryr::object_size(x)
#> 1.61 kB

Second, the predict() method is now faster for large data:

a <- data.frame(x = seq(100000))
microbenchmark::microbenchmark(predict(model, a), predict(x, a))
#> Unit: milliseconds
#>               expr       min        lq      mean    median        uq
#>  predict(model, a) 18.875002 22.784032 33.809279 24.919282 27.280293
#>      predict(x, a)  1.639926  1.915395  3.067028  2.165641  2.440346
#>       max neval
#>  90.07108   100
#>  50.03843   100

Third, the new object supports a conversion to a function using as.function(). This return value of this converion is a function which implements predict() as well, only now the compute time is much smaller:

f <- as.function(x)
microbenchmark::microbenchmark(predict(x, a), f(a))
#> Unit: microseconds
#>           expr      min       lq      mean   median       uq      max
#>  predict(x, a) 1631.693 1664.351 1924.7329 1724.274 2135.965 3426.342
#>           f(a)  185.949  208.481  390.2227  216.476  311.847 2296.787
#>  neval
#>    100
#>    100

craiggrabowski/predictr documentation built on May 28, 2019, 7:48 p.m.