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Data Mining and Visualization for Business Intelligence : case study

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Added on  2019-10-30

Data Mining and Visualization for Business Intelligence : case study

   Added on 2019-10-30

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DATA MINING AND VISUALIZATION FORBUSINESS INTELLIGENCEBusiness Case AnalysisStudent id[Pick the date]Question 1
Data Mining and Visualization for Business Intelligence : case study_1
Data and variable description (a)Principal component Analysis This is considered to be a powerful technique to reduce n- number of predictors into principalcomponents by evaluating the input variables. The resulting output for PCA on the given set ofvariables from XLMiner is shown below:Student ID & Name Page 1
Data Mining and Visualization for Business Intelligence : case study_2
Figure 1 : PCA OUTPUT FROM XLMINERAnalysis It can be viewed from variance % table that initial 5 principal components has more than 85% oftotal variation is associated with the eight (original) variable. Therefore it can be suggested toeliminate the rest three principal components because they do not have much influence on thescale of variables. The reduced matrix is given below:Student ID & Name Page 2
Data Mining and Visualization for Business Intelligence : case study_3

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