Normalization (Data Science): Revision history

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    5 November 2024

    • curprev 09:0409:04, 5 November 2024‎ 핵톤 talk contribs‎ 5,085 bytes +5,085‎ Created page with "Normalization in data science is a preprocessing technique used to adjust the values of numerical features to a common scale, typically between 0 and 1 or -1 and 1. Normalization ensures that features with different ranges contribute equally to the model, improving training stability and model performance. It is especially important in machine learning algorithms that rely on distance calculations, such as k-nearest neighbors (kNN) and clustering. ==Importance of Normali..." Tag: Visual edit
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