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What is Data Reduction Techniques in Data Science about?

The document discusses various data reduction techniques in data science, including Discrete Wavelet Transform (DWT), Principal Components Analysis (PCA), and attribute subset selection methods. It also covers sampling methods, data cube aggregation, and data transformation strategies such as normalization and discretization. Additionally, it introduces OLAP operations like roll-up, drill-down, slice, dice, and pivot for analyzing multidimensional data.

Author

p98070734

Language

EN