Developing machine learning-based models to predict intrauterine insemination (iui) success by address modeling challenges in imbalanced data and providing modification solutions for them

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• who: Sajad Khodabandelu from the Institute, Babol University of Medical Sciences, Babol, Iran have published the article: Developing machine learning-based models to predict intrauterine insemination (IUI) success by address modeling challenges in imbalanced data and providing modification solutions for them, in the Journal: (JOURNAL)
• what: To increase the performance of the models mutual information classification (MIC-FS) genetic algorithm (GA-FS) and random forest (RF-FS) were used to select the ideal feature sets for model development. The authors used three different methods to evaluate and compare the models which are as follows. The . . .
  

   

  

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