Judge3


This  is a simulated dataset which contains informations about   assessed by 3 experts to evaluate various product from six regions. 
This dataset (Judge1) contains 4 symbolic interval variables. 
In these data, the five successive pairs of columns represented the five symbolic variables of type interval.
Each pair consists of a min and a max.


This package implements an extension of principal component analysis (PCA) tailored to handle multiple data tables. It can handle Big Data in the sense that the variation in massive data can be described by intervals [a, b] and multiple tables.

Brahim Brahim

GPCSIV

GPCSIV, Generalized Principal Component of Symbolic Interval
variables

Judge3 function

A data frame with 6 observations on the following 8 variables.
  <dl>
    <dt><code>Banana.min</code></dt><dd>a numeric vector, minimum grade banana proposed by the expert 3</dd> <dt><code>Banana.max</code></dt><dd>a numeric vector, maximum grade banana proposed by the expert 3</dd> <dt><code>Coffee.min</code></dt><dd>a numeric vector, minimum grade coffee proposed by the expert 3</dd> <dt><code>Coffee.max</code></dt><dd>a numeric vector, maximum grade coffee proposed by the expert 3</dd> <dt><code>Thea.min</code></dt><dd>a numeric vector, minimum grade thea proposed by the expert 3</dd> <dt><code>Thea.max</code></dt><dd>a numeric vector, maximum grade thea proposed by the expert 3</dd> <dt><code>Cocoa.min</code></dt><dd>a numeric vector, minimum grade cocoa proposed by the expert 3</dd> <dt><code>Cocoa.max</code></dt><dd>a numeric vector, maximum grade banana proposed by the expert 3</dd> </dl> 

Judge3: GPCSIV, dataset Judge 3

Description

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Examples