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Using MCA and variable clustering in R for insights in customer attrition

April 21, 2017
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Using MCA and variable clustering in R for insights in customer attrition

Analytical challenges in multivariate data analysis and predictive modeling include identifying redundant and irrelevant variables. A recommended analytics approach is to first address the redundancy; which can be achieved by identifying groups of variables that are as correlated as possible among themselves and as uncorrelated as possible with other variable groups in the same data Related Post

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Web Scraping and Applied Clustering Global Happiness and Social Progress Index

April 9, 2017
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Web Scraping and Applied Clustering Global Happiness and Social Progress Index

Increasing amount of data is available on the web. Web scraping is a technique developed to extract data from web pages automatically and transforming it into a data format for further data analysis and insights. Applied clustering is an unsupervised learning technique that refers to a family of pattern discovery and data mining tools with Related Post

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