achieve


  Measurements at the beginning of the 4th grade (when the national
  average is 4.0) and of the 6th grade in 25 schools in New Haven. 


datasets

The main function kcca implements a general framework for
k-centroids cluster analysis supporting arbitrary distance
measures and centroid computation. Further cluster methods
include hard competitive learning, neural gas, and QT
clustering. There are numerous visualization methods for
cluster results (neighborhood graphs, convex cluster hulls,
barcharts of centroids, ...), and bootstrap methods for the
analysis of cluster stability.

Friedrich Leisch

flexclust

Flexible Cluster Algorithms

achieve function

A data frame with 25 observations on the following 4 variables.
  <dl>
    <dt>read4:</dt><dd>4th grade reading</dd> <dt>arith4:</dt><dd>4th grade arithmetic</dd> <dt>read6:</dt><dd>6th grade reading</dd> <dt>arith6:</dt><dd>6th grade arithmetic</dd> </dl> 

Format

<a href="http://www.uni-koeln.de/themen/statistik">http://www.uni-koeln.de/themen/statistik</a>

achieve: Achievement Test Scores for New Haven Schools

Description

Usage

Arguments

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Source

References