Jump to content

Z-score normalization: Difference between revisions

Created page with "{{see also|Machine learning terms}} ===Introduction== Data normalization in machine learning is a critical preprocessing step that helps boost the performance of many algorithms. Normalization involves scaling data to a specified range or distribution to reduce the impact of differences in scale or units of features. One widely-used technique for normalization is Z-score normalization (also referred to as standardization). ==What is Z-score normalization?== Z-score norm..."
(Created page with "{{see also|Machine learning terms}} ===Introduction== Data normalization in machine learning is a critical preprocessing step that helps boost the performance of many algorithms. Normalization involves scaling data to a specified range or distribution to reduce the impact of differences in scale or units of features. One widely-used technique for normalization is Z-score normalization (also referred to as standardization). ==What is Z-score normalization?== Z-score norm...")
(No difference)