tourData09

<p>Each row represents the performance of a rider in the
  2009 Tour de France; the name and team of the rider are used as the
  row names. The four columns are the <code>Cost</code> (to include on a team
  in the Versus fantasy challenge), <code>Scores</code> (based on daily
  finishing position), <code>JerseyBonus</code> (for any days spent in one of
  the three main leader jerseys), and <code>Total</code> (the sum of Scores
  and JerseyBonus).</p>

datasets

Defines classes and methods that can be used
to implement genetic algorithms for feature selection.  The idea is
that we want to select a fixed number of features to combine into a
linear classifier that can predict a binary outcome, and can use a
genetic algorithm heuristically to select an optimal set of features.

Kevin Coombes

GenAlgo

Classes and Methods to Use Genetic Algorithms for Feature
Selection

tourData09 function

<p>A data frame with 102 rows and 4 columns.</p>

tourData09: Tour de France 2009

Description

Usage

Arguments

Format