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Component analysis

What is it Component analysis?

Principal component analysis (PCA for short) is a technique used to simplify large amounts of data. Imagine you have a table with a large number of columns (information). Principal component analysis allows you to convert this data into fewer columns, while trying to retain as much of the original information as possible.

Where will you meet it?

PCA is used in many areas where large amounts of data are involved - for example, in scientific research, financial analysis, marketing and other fields. It is a useful tool for simplifying and visualizing data.

Similar and related terms:

  • PCA - Principal Component Analysis
  • Data Reduction - reducing the number of information in a dataset
  • Data Visualization - a technique for displaying data in a clear and visually appealing way

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