Data Classification Using Combination of Five Machine Learning Techniques

作     者：Md. Habibur Rahman Jesmin Akhter Abu Sayed Md. Mostafizur Rahaman Md. Imdadul Islam Md. Habibur Rahman;Jesmin Akhter;Abu Sayed Md. Mostafizur Rahaman;Md. Imdadul Islam

作者机构：Department of Computer Science and Engineering Jahangirnagar University Dhaka Bangladesh Institute of Information Technology Jahangirnagar University Dhaka Bangladesh 

出 版 物：《Journal of Computer and Communications》 (电脑和通信（英文）)

年 卷 期：2021年第9卷第12期

页      面：48-62页

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Co-Variance of Fuzzy Rule Objective Function Surface Plot Confusion Matrix Scatterplot and Accuracy of Detection 

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.