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Colon detection using Principal Component Analysis (PCA) and Support Vector Machine (SVM)

机译:使用主成分分析(PCA)和支持向量机(SVM)进行结肠检测

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摘要

Large intestine or colon has an important role in human digestion system including assimilation process, especially vitamin, mineral, and water, forming feces from leftovers food that has not function to body. Human life style including the type of food that consumed is affect to colon condition. Iridology as science used to knowing organs condition by iris can be alternative to early examination colon condition. The examination can be used in computerization with applying Principal Component Analysis (PCA) as feature extraction method and Support Vector Machine (SVM) as classification method in data input iris image.
机译:大肠或结肠在人体消化系统中具有重要作用,包括同化过程,尤其是维生素,矿物质和水,它们会从剩余的食物中排泄成粪便,而这些食物对人体没有作用。包括食用的食物类型在内的人类生活方式都会影响结肠状况。作为用于通过虹膜了解器官状况的科学的虹膜学可以替代早期检查结肠状况。该检查可通过将主成分分析(PCA)作为特征提取方法并将支持向量机(SVM)作为分类方法在数据输入虹膜图像中应用在计算机中。

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