Journal of Computer and Communications, 2021, 9, 48-62 https://www.scirp.org/journal/jcc ISSN Online: 2327-5227 ISSN Print: 2327-5219 DOI: 10.4236/jcc.2021.912004 Dec. 31, 2021 48 Journal of Computer and Communications Data Classification Using Combination of Five Machine Learning Techniques Md. Habibur Rahman 1 , Jesmin Akhter 2 , Abu Sayed Md. Mostafizur Rahaman 1 , Md. Imdadul Islam 1 1 Department of Computer Science and Engineering, Jahangirnagar University, Dhaka, Bangladesh 2 Institute of Information Technology, Jahangirnagar University, Dhaka, Bangladesh Abstract 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. Keywords Co-Variance of Fuzzy Rule, Objective Function, Surface Plot, Confusion Matrix, Scatterplot and Accuracy of Detection 1. Introduction In this paper five widely used methods: Fuzzy weighted rule, FIS, FCM, SVM and ANN are integrated in classification of Iris data. Several works related to the paper are mentioned in this section. In [1] authors use Adaptive Neuro-Fuzzy Inference System (ANFIS) and the Fuzzy Inference System (FIS) for professional blogger classification, where FIS provides better results compared to Classifica- tion Based on Associations (CBA). The combination of Artificial Neural Net- work (ANN) and ANFIS gives better classification, whereas the proposed ANFIS of the paper shows the best result which is 93%. The concept of FIS in data clas- sification is also found in [2], where fault of electrical transmission line is de- How to cite this paper: Rahman, Md.H., Akhter, J., Rahaman, A.S.Md.M. and Islam, Md.I. (2021) Data Classification Using Com- bination of Five Machine Learning Tech- niques. Journal of Computer and Communi- cations, 9, 48-62. https://doi.org/10.4236/jcc.2021.912004 Received: September 2, 2021 Accepted: December 28, 2021 Published: December 31, 2021 Copyright © 2021 by author(s) and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY 4.0). http://creativecommons.org/licenses/by/4.0/ Open Access