evaluate_problem

evaluate_problem.classification

evaluate_problem.regression

test

A vector of predictions for each row in the holdout set

prediction

The true observations for the dependent value in the holdout set

observations


Generic function for evaluation of test results


Provides wrapper functions for running classification and
regression tests using different machine learning techniques, such as Random
Forests and decision trees. The package provides standardized methods for
preparing data to suit the algorithm's needs, training a model, making
predictions, and evaluating results. Also, some functions are provided to run
multiple instances of a test.

Sjoerd van der Spoel

crtests

Classification and Regression Tests

evaluate_problem function

<ul>
<li> <code>classification</code>: Evaluate a classification test's results. Uses <code><a rd-options="caret" href="/link/confusionMatrix?package=crtests&version=0.2.1&to=caret" data-mini-rdoc="caret::confusionMatrix">confusionMatrix</a></code> to determine accuracy and other performance measures </li>
<li> <code>regression</code>: Evaluate a regression test's results
</li>
</ul>

evaluate_problem: Generic function for evaluation of test results

Description

Usage

Arguments

Value

Methods (by class)