K-Means和模糊K-Means在塞拉利昂水稻数据集上的应用

Sri Lankan journal of applied statistics Pub Date : 2020-12-15 DOI:10.4038/sljastats.v21i3.8062

R. Bangura, S. D. Johnson, O. Mbulayi

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引用次数: 0

摘要

由于k-means和模糊k-means被视为无监督降维学习技术，我们从2015年收集的农艺数据中提出了该技术的应用，以证明塞拉利昂8种不同类型水稻品种的模糊k均值优于k均值的效率。此外，我们还从剪影簇(片段)中识别出不同的水稻品种作为异常值。

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Application of K-Means and Fuzzy K-Means to Rice Dataset in Sierra Leone

As k-means and fuzzy k-means are regarded as unsupervised dimensional reduction learning techniques, we present an application of this technique from the Agronomic data collected in 2015 to demonstrate the efficiency of fuzzy k means over k means of eight different types of rice varieties in Sierra Leone. Also, we identified different rice varieties as outliers from the silhouette clusters (segment).

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Sri Lankan journal of applied statistics

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