ProcessRAI: Summarising RAI Output

In rai: Revisiting-Alpha-Investing for Polynomial Regression

Description

Processes the output from the rai function. Requires dplyr, tibble, and ggplot2 packages.

Usage

plot_ntest_rS(rawSum)

plot_ntest_wealth(rawSum)

## S3 method for class 'rai'
predict(object, newdata = NULL, alpha = NULL,
  omega = NULL, ...)

## S3 method for class 'rai'
summary(object, ...)

Arguments

rawSum	processed version of rai summary stored as a tibble with correct column parsing.
object	an object of class rai; expected to be the list output from the rai function.
newdata	an optional data frame in which to look for variables with which to predict. If omitted, the fitted values are used.
alpha	level of procedure.
omega	return from rejecting a test in Alpha-Investing (<= alpha).
...	additional arguments affecting the summary or predict methods.

Value

A list which includes the following components:

plot_rS	plot of the change in r.squared over time (number of tests conducted).
plot_wealth	plot of the change in r.squared over time (number of tests conducted).
experts	summary of expert performance: number of features, number of rejections, order in which they were added to the expert list.
tests	table of number of times features were tested: how many features tested k times; which expert(s) conducted tests.
epochs	in which epochs were tests rejected and the corresponding rejection thresholds.
stats	summary statistics: number of tests, number of epochs, bound on percentage reduction in ESS by adding a single feature, number of passes through to features, final r.squared, cost of raiPlus (0 for rai).
options	options given to RAI: algorithm, searchType, poly, startDegree, r.

Examples

  data("CO2")
  theResponse = CO2$uptake
  theData = CO2[ ,-5]
  rai_out = rai(theData, theResponse)
  summary(rai_out)  # summary information including graphs
  predict(rai_out)  # fitted values from selected model

rai documentation built on July 2, 2019, 5:02 p.m.