Multiple Correspondence Analysis (MCA) with FactoMineR (hobbies dataset) Magalie Houée-Bigot & François Husson
Import data setwd("C:/users/houee/Downloads") # select the working directory hobbies = read.table("data_MCA_Hobbies.csv", header=TRUE, sep=";") header=TRUE : indicates that the file contains the names of the variables sep=";" : indicates the fields separator (usually “;” or “,” for csv files) It is important to check that the import is well done summary(hobbies) ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ##
header=TRUE : indicates that the file contains the names of the variables sep=" ... O.fruity. O.passion. O.citrus. ## Sauvignon:5. Min. :2.143. Min. :0.5000. Min. :1.000 ..... v.test. Dim.3 cos2 v.test. ## Sauvignon. 0.230 | -0.099 0.001 -0.179 |.
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text-mining: number of times the word i is in the text j. ⢠solutions (acid, bitter, etc.) - answers (acid, bitter, etc.): number of persons who answer j for the stimulus i.
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that follow using a high-quality thin C/A glue. 1) Carefully remove the aileron from one of the wing panels. Note the position of the hinges. 2) Remove each hinge ...
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la voile faire de la planche à voile faire du canoë des gradins un terrain un spectateur une spectatrice un arbitre une équipe un joueur une joueuse un gardien de but ... Sports et Loisirs / Sports and Hobbies un vélo une bicyclette un coureur une co
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