What are Different Types of Vector Normalization?

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SUMMARY

The discussion focuses on vector normalization techniques, specifically "max-normalization" and "Euclidean normalization." Max-normalization involves dividing each element of a vector by its largest element, while Euclidean normalization divides by the vector's Euclidean length. The conversation highlights the importance of clearly specifying the type of normalization used, especially when dealing with negative components, which may require applying absolute values to maintain the norm property.

PREREQUISITES
  • Understanding of vector mathematics
  • Familiarity with normalization techniques
  • Knowledge of Euclidean norms
  • Basic concepts of absolute values in mathematics
NEXT STEPS
  • Research "max-normalization" techniques in data preprocessing
  • Explore "Euclidean normalization" and its applications in machine learning
  • Study the impact of negative values on normalization processes
  • Learn about different normalization methods in data science
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Data scientists, machine learning practitioners, and anyone involved in vector mathematics or data preprocessing will benefit from this discussion.

juliette sekx
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I want to write that I'm normalizing a vector, but I need to specify what TYPE of normalization I'm doing.

I want to say that I'm dividing each element by the largest element in the vector, rather than something else like dividing all elements by the Euclidean length of the vector or something like that.

Is there a word for these two types of normalization, so that I don't need to explain what I'm doing in words ?? Like for ex. "max-normalization" and "Euclidean Normalization" ??

If I said that I'm normalizing the elements to lie between 0 and 1, would it be obvious that I'm dividing each element by the largest element in the vector ??

THank you.
 
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juliette sekx said:
I want to write that I'm normalizing a vector, but I need to specify what TYPE of normalization I'm doing.

I want to say that I'm dividing each element by the largest element in the vector, rather than something else like dividing all elements by the Euclidean length of the vector or something like that.
So you use the maximum norm ...
Is there a word for these two types of normalization, so that I don't need to explain what I'm doing in words ?? Like for ex. "max-normalization" and "Euclidean Normalization" ??
... and the Euclidean norm.
If I said that I'm normalizing the elements to lie between 0 and 1, would it be obvious that I'm dividing each element by the largest element in the vector ??
No. This would not be the only possibility.
THank you.
Also you have to specify how you deal with negative components. You might lose the norm property if you don't apply absolute values first.
 

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