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Data Mining Assignment Sample

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Added on  2019-11-12

Data Mining Assignment Sample

   Added on 2019-11-12

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DATA MININGASSIGNMENTSTUDENT ID[Pick the date]
Data Mining Assignment Sample_1
Data Mining Question 1 Dimension Reduction Part (A) Principal Component Analysis (PCA) Number of variables = 8 XLMiner output is shown below:Evaluation and interpretation of the PCABased on the XLMiner output of variance analysis, it can be seen that 95% of variance isdescribed by the initial six principal components. Therefore, it is essential to reduce the principalcomponent matrix only for six components. 1
Data Mining Assignment Sample_2
Data Mining The major six principal components and their respective significant features is finishedbelow:In order to find the most critical features among the six components, these are defined based ontheir contribution in variances. The critical features would be x2, x6 and x7. When any particular variable is indicating the maximum or higher level of variances among theother variables, then it is critical to normalize the data. The level of variances would be determined based on the variance analysis output fromXLMiner. 2
Data Mining Assignment Sample_3

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