Implementasi Reduksi Fitur t-SNE Pada Clustering Gambar Head shape Nematoda

Muhammad Rizky Adriansyah, Mohammad Reza Faisal, A. Gafur, Radityo Adi Nugroho, I. Budiman, Muliadi Muliadi
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Abstract

In this research, clustering of nematode head shape images is carried out. In processing the picture, a feature extraction method is needed to find important information from the image to be processed. One of the feature extraction that can be used is the wavelet. After the image goes through feature extraction, 5624 features are generated; many features can result in a long computation time. Therefore, it is necessary to make feature reduction to reduce the number of features from 5624 to only 2 or 3 elements, one of the newest feature reduction methods that can be used is t-SNE. In this study, a comparison of the results of cluster quality between those using feature reduction and those not using feature reduction was carried out. Silhouette Index results obtained without feature reduction is 0.046, and after using the t-SNE feature reduction, there is a significant increase to 0.418. Keywords: Clustering; Extraction Features; Reduction Features; t-SNE; Wavelet
实现t-SNE特性的转导与图形线虫形状的集合
本研究对线虫头部形状图像进行聚类。在对图像进行处理时,需要一种特征提取方法,从待处理的图像中找出重要的信息。其中一个可以使用的特征提取是小波。图像经过特征提取后,生成5624个特征;许多特征可能导致较长的计算时间。因此,有必要进行特征约简,将5624个特征减少到只有2或3个元素,可以使用的最新特征约简方法之一是t-SNE。在本研究中,对使用特征约简和不使用特征约简的聚类质量结果进行了比较。未进行特征约简得到的廓形指数结果为0.046,使用t-SNE特征约简后得到的廓形指数结果显著增加到0.418。关键词:聚类;提取功能;还原功能;t-SNE;小波
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