callHierarchyTree {rchic}R Documentation

callHierarchyTree

Description

Reads the data, prepare the data and call hierarchyTree.

Usage

callHierarchyTree(fileName, contribution.supp = FALSE,
  typicality.supp = FALSE, computing.mode = 1, verbose = FALSE)

Arguments

fileName

name of the file containing the data

contribution.supp

boolean to compute the contribution of supplementary variables

typicality.supp

boolean to compute the typicality of supplementary variables

computing.mode

controls the computing mode: 1=classic implication, 2=classic implication+ confidence, 3=implifiance

verbose

boolean to give many details.

Details

This function allows you to compute the hierarchy tree. This tree is built with the cohesion index which is not symmetric. It is very important to keep this in mind. At the end of the computation we obtain the hierarchy tree, as follows. In this tree, couple of variables are gathered according to their cohesion measure. Significant levels are highlighted in red. A significant level means that the considered level is more significant than the previous level and than the next one. In the following figure and in all the cases, an expert must choose according to his knowledge what is the threshold in the hierarchy tree after which the cohesion measure is not significant for the data considered. In general the last classes in the hierarchy tree are not significant. Comparing the hierarchy tree with the similarity tree, we can see that the hierarchy tree contains a greater number of classes than the similarity tree. As the cohesion is not symmetric, we have an important information on the implication. In this example, we can observe that the strong class is: craftiness generally implies malignant. The second strongest class is: powerful generally implies strong. hierarchy.png

Author(s)

Raphael Couturier


[Package rchic version 0.27 Index]