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29 articles for “Naive Bayes algorithm”
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Disease Prediction Android Application using Machine Learning
Abstract: The rapid proliferation of internet technology and handled devices has opened up new avenues for an online healthcare system. There are instances where online medical help or healthcare advice is easier and faster to grasp than real world help. People often feel reluctant to go to hospital or visit doctors for minor symptoms. However, in many cases, these minor symptoms may trigger into a major health hazard. As online wellbeing …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 8, Issue 1, 2021 · pp. 1–9 Read article
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Comparative Analysis of a Lie Detector using Support Vector Machine, Naive Bayes, and Random Forest Algorithm with Speech to Text Conversion
Abstract: Lie detection, additionally known as deception detection, uses questioning techniques to determine truth and falsehood in response. Physiological responses like vital sign, blood pressure, heartbeat, and respiratory rate are used to discriminate between truth and lie. Once we lie, our blood pressure goes up, our heart beats quicker, we have a tendency to breathe faster (and our breathing slows once the lie has been told), and changes occur in our …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 9, Issue 1, 2021 · pp. 13–18 Read article
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Using Machine Learning to Analyse Football Teams and Predict the Outcome of a Football Match
Abstract: Football, as one of the most popular sports on the planet, has always attracted a large number of fans. Over 150 million men and women of all ages play it in over 200 countries. Modern football has seen a paradigm shift from being just one of the most physical sports to now being one of the most complex sports due to the involvement of multiple new factors such as Home …
Published in Journal of Communication Engineering & Systems Read article
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Using Machine Learning to Analyze Football Teams and Predict the Outcome of a Football Match
Abstract: Football, as one of the most popular sports on the planet, has always attracted a large number of fans. Over 150 million men and women of all ages play it in over 200 countries. Modern football has seen a paradigm shift from being just one of the most physical sports to now being one of the most complex sports due to the involvement of multiple new factors such as home …
Published in Journal of Communication Engineering & Systems · Vol. 12, Issue 1, 2022 · pp. 31–41 Read article
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Crop Disease Prediction by Machine Learning
Abstract: The classification of Crop can be classified into several methods. The data set of crop leaf illnesses, notably Bacterial Leaf Blight disease (BLB), a crop leaf disease with significant outbreaks throughout Thailand, and Brown Spot Crop disease (BSR), is classified employing image classification in this study. Additionally, image processing technology is used for identifying different types of crop leaf disease. These algorithms include the Random Forest, Decision Tree, Gradient Boost, …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 21–25 Read article
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Abusive Language Detection using ML
Abstract: Detection of abusive language in online content has become a serious problem in recent years. Abusive language is an expression that carries grimy phrases each withinside the context of jokes, threat, vulgar intercourse conservation, or to disrespect someone. Nowadays many people post toxic comments in the social media such as Facebook, Twitter, etc. Many researches have tried to do it using the regular expression and blacklists but this is not …
Published in Journal of Advancements in Robotics · Vol. 8, Issue 3, 2021 · pp. 1–7 Read article
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DISEASE PREDICTION SYSTEM USING MACHINE LEARNING
Abstract: Machine learning (ML) is a rising field. It already plays an important role in many fields, with projects of all sizes showing its positive impact. One such use of machine learning algorithms is in the healthcare field. Medical facilities need to be improved in order to make better decisions about patient diagnosis and treatment options. In this paper, we attempt to use the performance of Machine learning equipment in health …
Published in Journal of Control & Instrumentation · Vol. 12, Issue 2, 2021 · pp. 14–18 Read article
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Prediction of Disease by Symptoms Using Machine Learning
Abstract: Machine Learning and data mining, both play the most popular role in analyzing and prediction in the field of health organization. It also helps to uncover different and new patterns in medicinal science. This project is around prediction of disease with help of the symptoms. This project aims to propose a model which will be strongly trained in detecting common diseases so that few of the common diseases can be …
Published in Journal of Advancements in Robotics · Vol. 9, Issue 1, 2022 · pp. 8–11 Read article
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Implementation of Anticipating Rainfall Using Machine Learning
Abstract: Rainfall forecasting is crucial for many aspects of our national economy and should help prevent major seasonal droughts. Since agriculture is a beloved profession in many states, some Asian countries are economically hooked to decline. Previous precipitation info is beneficial. Farmers are cancerous in managing their crops, resulting in economic progress for the country. downfall prediction is hard for earth science scientists because of unordering time and unordered quantity of …
Published in International Journal of Satellite Remote Sensing · Vol. 1, Issue 1, 2023 · pp. 1–8 Read article
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Class Imbalance Reduction and Training Data Selection for Cross Project Defect Prediction
Abstract: The research aims to predict errors in a targeted project using data from other projects. This project is named as the Cross-Project Defect Prediction (CPDP). There are a number of ways available to improve the predictable performance of CPDP models. However, there is no comparison of modern methods. Predictability facilitates the rational distribution of testing resources by detecting software modules that may be problematic before releasing products. If a project …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 9, Issue 3, 2022 · pp. 12–20 Read article
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A Supervised Learning Approach for Toxic Comment Detection on Social Media Platforms
Abstract: Nowadays everyone uses social media platforms like X (formerly Twitter), Instagram, Facebook, etc. for various purposes. With the help of this, we share our opinions, ideas, and feelings. Generally, the datasets obtained from the internet are constructive; however, there is a significant proportion of toxic ones. The datasets are filtered to remove noise, and noise is removed in post-processing. The study initiates with the upload and preprocessing of a toxic …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 2, 2024 · pp. 7–14 Read article
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Sentiment Analysis of Twitter Data for Better Services of Airlines Using Classifier-Model Algorithms, AI, and NLP Techniques
Abstract: The rising attractiveness of social media sites and usage of social websites is to share information. Tweet, for instance, is a stage in which audiences direct, and examine posts recognized as “tweets,” and engage together in one-of-a-kind communities through feedback, comments, tweets, and reviews. There are so many companies that want tweets, comments, reviews, and analyses on their products and services, so they can improve their services, products, and customer …
Published in Current Trends in Information Technology · Vol. 12, Issue 3, 2022 · pp. 29–46 Read article
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Prediction of Mobile Phone Price Using Machine Learning Classifiers
Abstract: One cannot imagine one's life without mobile phones; in today's digital era, mobile phones have become a necessity for everyone to fulfil their various demands like messaging, communication, entertainment, productivity, research, shopping and many more. In a thriving market of mobile phones where new smartphones are launched every year with new advanced features and various designs, determining the expense of a mobile can be a trouble-some tasks for consumers. In …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 101–108 Read article
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An Experimental Approach of Machine Learning Algorithms to Detect Botnet DDoS Attacks
Abstract: Botnets are one of the threats in a network to hamper the quality of the network by disrupting theresources of the network. These Botnets can be controlled remotely by Botmaster. The Machine Learning Algorithms play a major role to detect and control the Botnets that cause to DDoS attacks, malwares and phishing attacks that are vulnerable to network resources. The DDoS attacks are most dangerous malware events that disrupt whole …
Published in Journal Of Network security · Vol. 10, Issue 3, 2022 · pp. 7–14 Read article
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Timely Diabetes Possibility Prediction Using AI Techniques
Abstract: The fastest chronic life-threatening disease affecting more than 422 million people globally is diabetes. The primary causes of type 2 diabetes are lifestyle choices and environmental factors. It is a slowgrowing disease which starts to develop metabolic factors long before they evolve into a disease and is formally diagnosed by a fasting sugar test. There are records of indications related to diabetes from 520 patients in the dataset that was …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 2, 2022 · pp. 37–47 Read article
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A Systematic Review for Heart Disease Prediction Using AIML Algorithms
Abstract: Cardiovascular diseases (CVDs), commonly known as heart diseases, have consistently held the position of being the primary global cause of mortality for many years. They are also the most serious illness in India and the rest of the world. So, a method that is reliable, accurate, and easy to use is needed to find these diseases early and start the right treatment. Using a variety of medical datasets, machine learning …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 3, 2023 · pp. 53–61 Read article
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Comparative Study of Machine Learning Algorithms for Detection of Breast Cancer
Abstract: Breast cancer continues to be the most commonly diagnosed cancer among women, with more than 2.3 million new cases diagnosed yearly worldwide. It is stated as the leading cause of cancer-related deaths. Therefore, this emphasizes the dire necessity for early diagnosis with a view to improving survival. Early diagnosis elevates the effectiveness of prediction and treatment. This research carries out a structured and analytical evaluation of various machine learning algorithms, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 113–129 Read article
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Computer Aided Diagnosis of Breast Cancer using Machine Learning Techniques
Abstract: Breast cancer is one of the significant health problems that lead to early mortality in women, especially those between 40 and 55 years of age all over the world. In recent years, the number of breast cancer cases among women has risen significantly, making early and accurate diagnosis more important than ever. Computer-aided diagnostic (CAD) tools have become valuable in supporting radiologists by enhancing the precision of breast cancer detection. …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 2, 2025 · pp. 1–11 Read article
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Comparative Analysis of Heart Disease Prediction System
Abstract: In the present world, where heart illnesses are on the rise, it is crucial to forecast these diseases. Performing the task on heart disease is a bit difficult and it must be finished precisely and successfully. Heart disease identification relies heavily on Machine Learning (ML) and data mining approaches. The primary focus of the review paper is that patients are easily prone to cardiac diseases depending on medical traits. Using …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 1, 2023 · pp. 1–6 Read article
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Algorithm for the prediction of cardiovascular disease (CVD)
Abstract: cardiovascular diseases (CVD) still claim a significant number of deaths globally and remain the number one killer with an annual death toll of nearly 17.9 million. While several medical advancements have been made, an early diagnosis is still hard to obtain, which often leads to worsening conditions and intricate treatment options. With the advancement of modern technology, Machine learning has demonstrated to be a miraculous tool which can greatly impact …
Published in Research and Reviews : A Journal of Immunology · Vol. 15, Issue 2, 2025 Read article