Classification of underdeveloped regions in Maluku using binary MARS

M. S. N. V. Delsen, M. Y. Matdoan
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引用次数: 0

Abstract

Based on Presidential Regulation Number 131 of 2015 on Determine of Underdeveloped Regions in 2015-2019, Maluku ranks 4th out of 23 provinces. Maluku has 11 regions, 8 of them are classified as underdeveloped regions. Classification of underdeveloped regions can be done using statistical analysis, namely the Binary Multivariate Adaptive Regression Spline (MARS). So, specific objectives to be achieved in this study are to determine the best Binary MARS model for classification and to calculate the accuracy of the Binary MARS model for the classification of underdeveloped regions in Maluku. After obtaining the classification results, we find out of GCV value for the MARS Binary model was 0.155 and the R2 value is 0.897. This model provided 100% accuracy in classifying the underdeveloped regions in Maluku.
马鲁古欠发达地区二元MARS分类
根据2015年第131号总统令“2015-2019年不发达地区的确定”,马鲁古在23个省中排名第4位。马鲁古有11个地区,其中8个被列为欠发达地区。欠发达地区的分类可以使用统计分析,即二元多元自适应回归样条(MARS)。因此,本研究要实现的具体目标是确定最佳的Binary MARS分类模型,并计算Binary MARS模型对马鲁古欠发达地区分类的精度。得到分类结果后,我们发现MARS Binary模型的GCV值为0.155,R2值为0.897。该模型对马鲁古欠发达地区的分类准确率为100%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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