Should I Normalize My Data for Host Ranking?

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Normalizing data for host ranking can enhance the accuracy of predictions derived from measures like transmission and computation time. The effectiveness of normalization depends on the decision-making context and the specific goals of the analysis. A cost function is essential to determine the appropriate weight for each measure, guiding the normalization process. Without proper weighting, the combined measures may not provide a reliable ranking. Ultimately, normalization should align with the intended outcomes of the ranking system.
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I have 2 measures that I am using to rank terms that I get them by prediction (using linear regression). They are the time to transmit X bytes and the time to compute the X bytes. I do the prediction if I execute in host A, B, and C. I add the 2 measures and rank the hosts. I think adding these 2 measures are not enough. Should I normalize these 2 measures?
 
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It depends what decision will be based on the result. You need a cost function which tells you how much weight to give to each measure.
 
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