Diagnosis of chronic kidney disease based on support vector machine by feature selection methods

H Polat, H Danaei Mehr, A Cetin - Journal of medical systems, 2017 - Springer
… as wrapper feature selection methods … Naïve Bayes and Decision Tree-J48, on selected
subsets and compared the performance of the classifiers. Results have shown that Naïve Bayes

Artificial bee colony algorithm for feature selection and improved support vector machine for text classification

J Balakumar, SV Mohan - Information Discovery and Delivery, 2019 - emerald.com
feature selection, evaluates the efficiency of the ABCFS algorithm and improves the support
vector machine. … ) proposed the feature selectors and feature weights with Naive Bayes and …

A cardiotocographic classification using feature selection: a comparative study

SE Prasetyo, PH Prastyo, S Arti - JITCE (Journal of Information …, 2021 - jitce.fti.unand.ac.id
classification algorithms including Naïve Bayes, J48, Random Forest, Logistic Regression,
K-Nearest Neighbors, Support Vector Machines, … learning is Support Vector Machine. This …

Comparative review of feature selection and classification modeling

MA Azhar, PA Thomas - 2019 International conference on …, 2019 - ieeexplore.ieee.org
… than the other data mining techniques Naïve Bayes and J48. … as a support vector machine.
This is also called a supervised … is known as Naïve Bayes. It is also a supervised learning …

Early detection of diabetes mellitus using feature selection and fuzzy support vector machine

RB Lukmanto, A Nugroho, H Akbar - Procedia Computer Science, 2019 - Elsevier
… Forest and Support Vector Machines; and the results show that J48 decision … machine
learning framework such as Naïve Bayes, Decision Tree and Support Vector Machine by using

Feature selection and classification using support vector machine and decision tree

B Durgalakshmi, V Vijayakumar - Computational Intelligence, 2020 - Wiley Online Library
… 82.78% for all the features and 86.34% for features selected. The accuracy for the proposed
algorithm is high when compared to other features selection like Naïve Bayes, K-the nearest …

[HTML][HTML] Computer-aided decision-making for predicting liver disease using PSO-based optimized SVM with feature selection

JH Joloudari, H Saadatfar, A Dehzangi… - Informatics in medicine …, 2019 - Elsevier
… However, The Naïve Bayes algorithm has the fastest runtime … proposed classification models
and found that the J48 model … five classification models including support vector machine, …

[PDF][PDF] Cluster Analysis-Based Approach Features Selection on Machine Learning for Detecting Intrusion.

MN Aziz, T Ahmad - International Journal of Intelligent Engineering & …, 2019 - inass.org
… The first classification uses Support Vector Machine (SVM) with linear kernels, which finds
… IDS applications using three classification methods: SVM, Naïve Bayes, and J48. The first …

… cancer survivability prediction based on performance using classification techniques of support vector machines, C4. 5 and Naive Bayes algorithms for healthcare …

KR Pradeep, NC Naveen - Procedia computer science, 2018 - Elsevier
J48 classifier, an enhanced algorithm of C4.5 utilizes entropy and generates a decision tree.
C4.5 algorithm recognizes the main attribute … gives the details of the features selected along …

A composite hybrid feature selection learning-based optimization of genetic algorithm for breast cancer detection

AA Farid, G Selim, H Khater - 2020 - preprints.org
j48 classifier (61.98%) and naive Bayes of (43.27%), Jrip … high accuracy when using a
support vector machine (SVM) as … Lu, Incorporating feature selection method into support vector