文章基本信息

标题：Data Classification Using Combination of Five Machine Learning Techniques
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作者：Md. Habibur Rahman ; Jesmin Akhter ; Abu Sayed Md. Mostafizur Rahaman 等
期刊名称：Journal of Computer and Communications
印刷版ISSN：2327-5219
电子版ISSN：2327-5227
出版年度：2021
卷号：9
期号：12
页码：48-62
DOI：10.4236/jcc.2021.912004
语种：English
出版社：Scientific Research Publishing
摘要：Data clustering plays a vital role in object identification. In real life we mainly use the concept in biometric identification and object detection. In this paper we use Fuzzy Weighted Rules, Fuzzy Inference System (FIS), Fuzzy C-Mean clustering (FCM), Support Vector Machine (SVM) and Artificial Neural Network (ANN) to distinguish three types of Iris data called Iris-Setosa, Iris-Versicolor and Iris-Virginica. Each class in the data table is identified by four-dimensional vector, where vectors are used as the input variable called: Sepal Length (SL), Sepal Width (SW), Petal Length (PL) and Petal Width (PW). The combination of five machine learning methods provides above 98% accuracy of class identification.
关键词：Co-Variance of Fuzzy Rule;Objective Function;Surface Plot;Confusion Matrix;Scatterplot and Accuracy of Detection