การเปรียบเทียบประสิทธิภาพในการทำนายผลการจำแนกเมล็ดพันธุ์ข้าวเปลือกขาวดอกมะลิ 105 ด้วยเทคนิคการทำเหมืองข้อมูล

Main Article Content

สายชล สินสมบูรณ์ทอง

Abstract

In this study, an efficiency comparison in prediction of Khao Dok Mali 105 paddy rice classification with data mining techniques was compared. The seven classification methods were the followings: (1) k-nearest neighbor method using IBk algorithm; (2) decision tree method using J48 algorithm; (3) artificial neural network method using multilayer perceptron algorithm; (4) support vector machine method using polynomial kernel; (5) rule-based method using decision table algorithm; (6) binary logistic regression method; and (7) naïve Bayes method. The following efficiency comparisons of classification were employed: accuracy, recall, F-measure, and mean square error (MSE). The important results are as follows. The k-nearest neighbor method using random seed = 10, 20 and 30 showed the best accuracy, recall, F-measure, and MSE at 100 %, 1.000, 1.000 and 0.00002 respectively. The support vector machine method and rule-based using random seed = 10, and 20 exhibited the best recall at 1.000. Since the k-nearest neighbor method offered the best efficiencies for all the 4 values, it was considered the best prediction method.

Keywords

Article Details

Section
วิทยาศาสตร์กายภาพ
Author Biography

สายชล สินสมบูรณ์ทอง

ภาควิชาสถิติ คณะวิทยาศาสตร์ สถาบันเทคโนโลยีพระจอมเกล้าเจ้าคุณทหารลาดกระบัง ถนนฉลองกรุง เขตลาดกระบัง กรุงเทพมหานคร 10520

References

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