https://ask.ghassem.com/tag/normalizing Powered by Question2Answer https://ask.ghassem.com/259/feature-scaling-standardization-vs-normalization Hi,<br /> <br /> After learnt feature scaling, I have some questions regarding Normalization.<br /> <br /> Standardization: rescales data to have a mean of 0 and standard deviation of 1 after a data distribution is selected.(Please correct me if I understood it wrong)<br /> <br /> Normalization: rescale data into a range of 0-1.(Please correct me if I understood it wrong)<br /> <br /> Questions:<br /> <br /> 1. in what cases we use standardization? when to use normalization? when to use a combined method?<br /> <br /> 2. In class, features are standardized first using N(0,1), then Z score can be standardized to some number between 0-1. How is Z score standardized? (what Z score will be 0 and what Z score will be 1?) if we use different data set, will Z score with same value always reach to same standardized result? Can this standardization formula be stored so we can reproduce the same standardization &nbsp;for prediction purpose?<br /> <br /> Thanks a lot for your help. Machine Learning https://ask.ghassem.com/259/feature-scaling-standardization-vs-normalization Wed, 03 Oct 2018 16:41:16 +0000 https://ask.ghassem.com/169/possible-convert-normalized-number-the-original-raw-number <p>Please see example from the following <a rel="nofollow" href="https://stackoverflow.com/questions/36593665/undo-l2-normalization-in-sklearn-python">link</a>.</p> <p>The question is leaning towards a programming code solution in Python as the link above shows. Involving sklearn&nbsp;and&nbsp;any other Python libraries.</p> <p>Relative to the link, could there be a manual solution for L1 as well?</p> <p>Could x include more dimensions for manual solutions? For example:</p> <p>([[4,6,9,3], [8,1,2,5]])</p> Machine Learning https://ask.ghassem.com/169/possible-convert-normalized-number-the-original-raw-number Thu, 27 Sep 2018 23:33:02 +0000