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10. Finding Independent Features > Non-Negative Matrix Factorization

Non-Negative Matrix Factorization

The technique for extracting the important features of the data is called non-negative matrix factorization (NMF). This is one of the most sophisticated techniques covered in this book, and it requires a bit more explanation and a quick introduction to linear algebra. Everything you need to know will be covered in this section.

A Quick Introduction to Matrix Math

To understand what NMF is doing, you’ll first need to understand a bit about matrix multiplication. If you’re already familiar with linear algebra, you can safely skip this section.

An example of matrix multiplication is shown in Figure 10-2.

Example of matrix multiplication

Figure 10-2. Example of matrix multiplication


  

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