Text Mining on Wine Description

Here is an example of text mining with correspondence analysis.
Within the context of research into the characteristics of the wines from Chenin vines in the Loire Valley (French wines), a set of 10 dry white wines from Touraine were studied: 5 Touraine Protected Appellation of Origin (AOC) from Sauvignon vines, and 5 Vouvray AOC from Chenin vines.
degustationThese wines were described by 12 professionals. The instructions were: for each wine, give one or more words which, in your opinion, characterises the sensory aspects of the wine. This data was brought together in a table with the wines as rows and the columns as words, where the general term Xij is the number of times that a word j was associated with a wine i (data are available here).

This contingency table has been analysed using Correspondence Analysis (CA) to provide an image summarising the diversity of the wines. Continue reading

Interactive plots in PCA with Factoshiny

A beautiful graph tells more than a lenghtly speach!!

So it is crucial to improve the graphs obtained by Principal Component Analysis or (Multiple) Correspondence Analysis. The package Factoshiny allows us to easily improve these graphs interactively.

The package Factoshiny makes interacting with R and FactoMineR simpler, thus facilitating selection and addition of supplementary information. The main advantage of this package is that you don’t need to know the lines of code, and moreover that you can modify the graphical options and see instantly how the graphs are improved. You can visualize this video to see how to use Factoshiny.


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