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Comparation analysis of naïve bayes and decision tree C4.5 for caesarean section prediction
2021
Journal of Soft Computing Exploration
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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
2020
International Journal of Innovative Science and Research Technology
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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
2012
Second International Conference on the Innovative Computing Technology (INTECH 2012)
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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
2013
International Journal on Computational Science & Applications
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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
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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
2020
International Journal of Interactive Multimedia and Artificial Intelligence
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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
2022
BioMed Research International
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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
2011
Journal of Software Engineering and Applications
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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
2018
International Journal of Electrical and Computer Engineering (IJECE)
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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
2021
International Journal of Advanced Computer Science and Applications
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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
A CLASSIFICATION APPROACH FOR NAÏVE BAYES OF ONLINE RETAILERS
2017
Acta Informatica Malaysia
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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
2014
International Journal of Computer Applications
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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)
2020
European Journal of Electrical Engineering and Computer Science
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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
2022
JURNAL TEKNIK INFORMATIKA
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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
PROJECT DISPUTE PREDICTION BY HYBRID MACHINE LEARNING TECHNIQUES
2013
Journal of Civil Engineering and Management
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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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