Seven Techniques for Data Dimensionality Reduction Missing Values , Low Variance Filter , High Correlation Filter , PCA , Random Forests , Backward Feature Elimination , and Forward Feature Construction

The recent explosion of data set size, in number of records as well as of attributes, has triggered the development of a number of big data platforms as well as parallel data analytics algorithms. At the same time though, it has pushed for the usage of data dimensionality reduction procedures.