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Comparation analysis of naïve bayes and decision tree C4.5 for caesarean section prediction

2021 Journal of Soft Computing Exploration  
The objective of this research is to predicte and analyse caesarean section using C4.5 and Naïve Bayes classifier models.  ...  The accuracy using C4.5 by 80 training cases is 45% And the accuracy using Naïve Bayes is 50%.  ...  The methods that will be used in this project are comparation of the Decision Tree C4.5 and Naïve Bayes methods to classify the caesarean section.  ... 
doi:10.52465/joscex.v2i1.25 fatcat:jbcghvtjyjfifehiowcnmnkulq

A Predictive Risk Model for Software Projects' Requirement Gathering Phase

Beatrice O. Akumba, Samera U. Otor, Iorshase Agaji, Barnabas T. Akumba
2020 International Journal of Innovative Science and Research Technology  
A supervised machine learning technique was used to predict the risk across the projects using Naïve Bayes Classifier technique.  ...  The model was able to predict the risks across the projects and the performance metrics of the risk attributes were evaluated.  ...  They developed a success/failure rate risk prediction algorithm using Naïve Bayes classifier techniques on the data collected.  ... 
doi:10.38124/ijisrt20jun066 fatcat:3ylwkddf3bhkdbjamp4txzdide

Baeza-Yates and Navarro approximate string matching for spam filtering

Monther Aldwairi, Yahya Flaifel
2012 Second International Conference on the Innovative Computing Technology (INTECH 2012)  
The proposed approach achieves 97.2% overall accuracy with a simple Naïve Bayes classifier.  ...  Spam has evolved in terms of contents, methods, delivery networks and volume. Reports indicate that up to 90% of the World Wide Web email traffic is spam [1].  ...  In order to improve system performance, a better classifier than the simple Naïve Bayes is to be used.  ... 
doi:10.1109/intech.2012.6457802 fatcat:bgs5gogo4zddfjwpgw25l6anie

An Analysis on the Performance of Naive Bayes Probabilistic Model Based Classifier for Cardiotocogram Data Classification

Sundar C, Chitradevi M, Geetharamani G
2013 International Journal on Computational Science & Applications  
The CTG, which is one of the most common diagnostic techniques used to evaluate maternal and fetal well-being during pregnancy and before delivery.  ...  In this paper, we evaluate machine learning based Naine Bayes probabilistic model based classifier for their suitability towards classifying CTG data.  ...  The derived results clearly show Naïve Bayes probabilistic model based classifier can be used for the classification of CTG data.  ... 
doi:10.5121/ijcsa.2013.3103 fatcat:vdshkpdtbzgrlbhctrn7xpwpqm

Breast Cancer Dataset Classification using Neural Network

2019 International Journal of Engineering and Advanced Technology  
Scrum is one of the most vital frameworks used when working towards Agile Software Development projects.  ...  But, the way of customizing the process and giving a minimal feature delivery at the end of each Sprint in the projects act as a major challenge.  ...  Naïve Bayes is one of the well known classification algorithm. It is mostly used when probability prediction belongs to particular class.  ... 
doi:10.35940/ijeat.f9522.088619 fatcat:upxu2pvmxfb27oalxrkpa24tpq

NSL-BP: A Meta Classifier Model Based Prediction of Amazon Product Reviews

Pravin Kumar, Mohit Dayal, Manju Khari, Giuseppe Fenza, Mariacristina Gallo
2020 International Journal of Interactive Multimedia and Artificial Intelligence  
Then, by adopting a stacking ensemble model, we combine Naïve Bayes, Logistic Regression, and SVM to predict the ratings. We will combine these models into a two-level stack.  ...  In the literature, many research projects work on the rating prediction of a given review.  ...  Naïve Bayes Naïve Bayes classifiers belong to the family of probabilistic classifiers that apply the Bayes's theorem [32] , [33] .  ... 
doi:10.9781/ijimai.2020.10.001 fatcat:hqxutacqibcdhaumgfivp2xdqi

An Image Processing Approach for Detection of Prenatal Heart Disease

Saravana Selvan, S. John Justin Thangaraj, J. Samson Isaac, T. Benil, K. Muthulakshmi, Hesham S. Almoallim, Sulaiman Ali Alharbi, R. R. Kumar, Sojan Palukaran Thimothy, Yuvaraja Teekaraman
2022 BioMed Research International  
The purpose of this research is to predict whether or not a person will develop cardiovascular disease. According to the statistics, naïve Bayes classifier has the highest overall accuracy.  ...  Considering their relevance in establishing the usefulness of alternate approaches, only 15 of the 75 criteria are examined.  ...  This project was supported by Researchers Supporting Project number (RSP-2022/283), King Saud University, Riyadh, Saudi Arabia.  ... 
doi:10.1155/2022/2003184 pmid:35958813 pmcid:PMC9363204 fatcat:d4ki7a2nwreszckd6hx5uc4gju

Defect Prediction Leads to High Quality Product

Naheed Azeem, Shazia Usmani
2011 Journal of Software Engineering and Applications  
Defect prediction is relatively a new research area of software quality assurance. A project team always aims to produce a quality product with zero or few defects.  ...  It describes the key areas of software defect prediction practice, and highlights some key open issues for the future.  ...  Using decision threshold optimization on Naïve Bayes classifier, probability of false alarm (pf) rate has decreased, while Balance rate has increased and the probability of detection (pd) rates remained  ... 
doi:10.4236/jsea.2011.411075 fatcat:4myguuo6gngzfczxm6je4snxy4

Analysis of Mobile Service Providers Performance Using Naive Bayes Data Mining Technique

M. A. Burhanuddin, Ronizam Ismail, Nurul Izzaimah, Ali Abdul-Jabbar Mohammed, Norzaimah Zainol
2018 International Journal of Electrical and Computer Engineering (IJECE)  
This project bring insights of how the telecommunication industries can analyze tweet data from their customers.  ...  will be used as a reference.  ...  for the financial support in this project.  ... 
doi:10.11591/ijece.v8i6.pp5153-5161 fatcat:w7vf44p42bgmbh623cf2ytf77e

Predicting the Appropriate Mode of Childbirth using Machine Learning Algorithm

Md. Kowsher, Nusrat Jahan Prottasha, Anik Tahabilder, Kaiser Habib, Md. Abdur-Rakib, Md. Shameem Alam
2021 International Journal of Advanced Computer Science and Applications  
The mode of baby delivery is genuinely vital to a delivery patient and her infant child. It might be a crucial factor for ensuring the safety of both the mother and the child.  ...  We have also analyzed the result and compared them using various statistical parameters to determine the bestperformed model.  ...  Also, from the section of naive Bayes algorithms, we can figure out that Gaussian naive Bayes has shown the best accuracy of 0.874381 and its F1 score is 0.872635 among all naive Bayes classifiers.  ... 
doi:10.14569/ijacsa.2021.0120582 fatcat:6clrjonjzbcbbjqmizojjafry4


Aida Mustapha, Shazwani Mustapa, Nurfarahim Md.Azlan, Noor Fatin Ishmah Saifarrudin, Shahreen Kasim, Mohd Farhan Md Fudzee, Azizul Azhar Ramli, Hairulnizam Mahdin, Seah Choon Sen
2017 Acta Informatica Malaysia  
On the basis of the Recency, Frequency, and Monetary model, customers of the business have been segmented into various meaningful groups using the classification and naïve bayes algorithm, and the main  ...  In this article a case study of using data mining techniques in customer-centric business intelligence for an online retailer is presented.  ...  In this paper, we try to give the basic concept of classification technique using naïve bayes Support vector that can be used for classifying the unknown records [2-4]. Experiment a.  ... 
doi:10.26480/aim.01.2017.26.28 fatcat:geshrceoofb4zb4facb6rzkkqm

Spam Email Detection using Structural Features

Sarju S, Riju Thomas, Emilin Shyni C
2014 International Journal of Computer Applications  
In this paper we tend to project a replacement methodology to segregate spam emails from nonspam (legitimate) emails using the distinct structural features available in them.  ...  In recent years, we have witnessed a dramatic raise in the use of web and thus email becomes an inevitable mode of communication.  ...  Naïve Bayes classifier is based on Bayes theorem [14] .  ... 
doi:10.5120/15485-4265 fatcat:iysduocw6beqpildhcwkz23rzu

Training of the Naïve Bayes Classifier for the Detection of the Power Quality Events (Voltage Dip, Voltage Swell and Voltage Interruption)

Oluwaseun Elijah Adegbite, M. O. Okelola
2020 European Journal of Electrical Engineering and Computer Science  
train the Naïve Bayes classifier to develop a classifier that is capable of classifying waveform signals that has such disturbances in them.  ...  The paper is based on the classification of Voltage Dip, Voltage Swell and Voltage Interruption using the STFT as the method of the detection of the triggering point and using such synthetic signal to  ...  Synthetic signals was generated using the Short Time Fourier Transform for the purposes of the training of the Naïve Bayes classifier.  ... 
doi:10.24018/ejece.2020.4.4.222 fatcat:zwbbllw7hfblxmokz4sq4q3kj4

Sentiment Analysis of Public Opinion Covid-19 Vaccine Using Naïve Bayes and Random Forest Methods

Ines Sholekha, Ahmad Faqih, Agus Bahtiar
The results of this study yielded 89.79% for Naïve Bayes and 84.62% for Random Forest. Indonesians are giving positive responses to the administration of the COVID-19 vaccine.  ...  The purpose of this study is to identify the community response to the vaccine so that the right strategy can be used.  ...  The above results, therefore, lead to the conclusion that, in this study, the classification of Naïve Bayes is the best because it produces more accurate and precise predictions with an accuracy rate of  ... 
doi:10.15408/jti.v15i1.24847 fatcat:fwqvf353rrcvzgvcxymecj6uq4


Jui-Sheng Chou, Chih-Fong Tsai, Yu-Hsin Lu
2013 Journal of Civil Engineering and Management  
The single classification techniques utilized are multilayer perceptron (MLP) neural networks, decision trees (DTs), support vector machines, the naïve Bayes classifier, and k-nearest neighbor.  ...  This study demonstrates the efficiency and effectiveness of hybrid machine learning techniques for early prediction of dispute occurrence using conceptual project information as model input.  ...  Naïve Bayes classifier The naïve Bayes classifier requires all assumptions be explicitly built into models that are then utilized to derive 'optimal' decision/classification rules.  ... 
doi:10.3846/13923730.2013.768544 fatcat:2wjzt3hh65f6pf3d4vjdoa7nem
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