Gökhan Aksu|Cem Oktay Güzeller|Mehmet Taha Eser
The Effect of the Normalization Method Used in Different Sample Sizes on the Success of Artificial Neural Network Model
Adnan Menderes University|Akdeniz University Hospital|Akdeniz University Hospital
study aimed compare different normalization methods employed model developing process via artificial neural networks different sample sizes part comparison normalization methods input variables set work discipline environmental awareness instrumental motivation science selfefficacy weekly science learning time covered pisa 2015 whereas students science literacy level defined output variable amount explained variance statistics correct classification ratios used comparison normalization methods discussed study dataset analyzed matlab2017b software prediction classification algorithms used study according findings study adjusted minmax normalization method yielded better results terms amount explained variance different sample sizes compared normalization methods significant difference found correct classification rates according normalization method data lacked normal distribution possibility overfitting taken consideration working small samples modelling process artificial neural network addition also found sample size significant effect classification prediction analyzes performed artificial neural network methods result study concluded sample size 1000 consistent results obtained studies performed artificial neural networks field education