|Table of Contents|

Loyalty prediction method based on improvednearest neighbor algorithm(PDF)

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2017年04期
Page:
448-
Research Field:
Publishing date:

Info

Title:
Loyalty prediction method based on improvednearest neighbor algorithm
Author(s):
Zhu HongLi QianmuQi Yong
School of Computer Science and Engineering,Nanjing University of Science and Technology,Nanjing 210094,China
Keywords:
data mining classification clustering regression nearest neighbor algorithm bayesian algorithm loyalty prediction
PACS:
TP391
DOI:
10.14177/j.cnki.32-1397n.2017.41.04.008
Abstract:
In order to improve the accuracy and efficiency of loyalty prediction,this paper,combining K nearest neighbor(KNN)with Bayesian algorithm as a classification prediction method,proposes a loyalty prediction method based on improved nearest neighbor.The method first takes high loyal customers and low loyal customers as the same category of loyal customers.The method classifies the data set with Bayesian algorithms to obtain non-loyal customers and loyal customers.It takes loyal customers as test data set of the following KNN algorithm and classifies them to obtain high loyal customers,low loyal customers and non-loyal customers.The experimental results show that this method can not only reduce the impact of the K value on the nearest neighbor algorithm and reduce its memory overhead,but also can effectively shorten the time of loyalty classification and improve the accuracy of the classification accuracy.

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Last Update: 2017-08-31