Machine learning modeling for the prediction of plastic properties in metallic glasses

HIGHLIGHTS

• who: Nicolu00e1s Amigo from the Facultad de Ingenieru00eda have published the Article: Machine learning modeling for the prediction of plastic properties in metallic glasses, in the Journal: Scientific Reports Scientific Reports
• what: In this work, u03c3Y was calculated following the offset criterion | Vol:.(1234567890) 13:348 | 6 ni=1 di2 u03c1=1-, n(n2 - 1) where di is the difference between the two ranks of the pair of features, and n is the number of observations. This work showed that prediction of materials properties benefits from these state of the art techniques.
• how . . .
  

   

  

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