Comparison Backpropagation (BP) and Learning Vector Quantification (LVQ) on classifying price range of smartphone in market

Abstract

In this time, there are many smartphones sold in market with various price. The price of smartphone depends on some components such as weight, internal storage, memory (RAM), rear camera, front camera and brands. In this research, there are two methods for classifying price range of smartphone in market, i.e. Backpropagation (BP) and Learning Vector Quantization (LVQ). From classifying price range of smartphone in market using BPand LVQ, there are the differences on the both of them. BP classifies price range of smartphone by gradient descent of target and output on its iteration. LVQ classifies price range of smartphone by euclideandistance of weight and data on its iteration. Based on simulations, BP gives better accuracy value with value 88.75 % in training data and 87.5 % in testing datathan LVQ with value 81.25 % in training data and 72.5 % in testing data