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167 articles for “and Random forest”
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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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Optimizing Sentiment Analysis with Naïve Bayes and Random Forest Techniques: A Result-based Approach
Abstract: In the increased digitalization, the sentiment analysis and classification have evolved as an eminent area to determine the polarity of positive, negative, and neutral reviews of the customers and users on products. It is an integral application field that employs supervised learning, Machine Learning, and Natural Language Processing concepts. The proposed Semantic Analysis and Classification using Naive Bayes and Random Forest system accomplishes the sentiment polarity by classifying the user …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 46–57 Read article
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Detection of Phishing Website URLs and Email/SMS Using Random Forest and Multinomial Naive Bayes
Abstract: Currently, phishing attacks via SMS/email and URL have become significant threat to cybersecurity, posing risks to both individuals and organizations alike. Phishing attacks typically involve the creation of fraudulent websites or the dissemination of deceptive emails and SMS messages to trick users into disclosing sensitive information such as passwords, credit card numbers or personal details. To respond to these attacks, we develop a robust system for the detection of phishing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 22–30 Read article
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Cloud-driven Fraud Detection: Evaluating Decision Tree and Random Forest Classifiers for Credit Card Transaction Security
Abstract: With the alarming rise in global financial fraud, necessitating substantial annual losses, modern techniques for fraud detection are continuously evolving across various business domains. Fraud detection involves constant monitoring of user activities to estimate, perceive, or prevent undesirable behaviour. Cloud Computing emerges as a promising solution, accelerating application deployment, fostering creativity and innovation, reducing costs, and enhancing overall business acumen. This study introduces a cloud-driven approach to fraud detection, specifically …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 13–27 Read article
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Optimizing Marketing Campaigns Using Random Forest and A/B Testing
Abstract: Marketing initiatives play a vital role in driving business growth by reaching targeted consumer segments through tailored strategies across multiple channels. The success of these initiatives is influenced by various factors, including the type and duration of the campaign, the characteristics of the target audience, the communication channels employed, and the overall efficiency of each strategy. These factors collectively impact key performance metrics such as conversion rates, customer acquisition costs, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 01–09 Read article
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Monitoring and Controlling System of COVID-19 Symptoms Using Random Forest
Abstract: Corona virus (COVID-19) has already claimed hundreds of lives and infected millions of people around the world. The early detection of COVID-19 is shown in this paper. Machine learning random forest techniques were used to implement the detection procedure on cloud computing. Objectives of the study is to provide health assurance directly from home using some smart tools with cloud computing. Our research contribute the categorization of patients into different …
Published in Research and Reviews : Journal of Computational Biology · Vol. 11, Issue 1, 2022 · pp. 22–29 Read article
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A Random Forest Approach to Navigating Cryptocurrency Market Fluctuations
Abstract: This study looks at the main elements influencing daily price variations to improve our analysis and prediction of Bitcoin values. Our forecasting algorithm is based on comprehensive data that we have collected and analyzed over the last few years. Because the Random Forest algorithm provides more accurate forecasts than previous techniques, that is why we chose it. Predicting the price swings of cryptocurrencies, like Bitcoin, can be challenging due to …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 2, 2024 · pp. 7–11 Read article
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Forecasting of Crushing Strength of Sustainable Concrete by Employing Deep and Random Forest Machine Learning
Abstract: Sustainable concrete is one of the milestone of the concrete industry. This concrete fulfills the requirements of concrete manufacturing industry such as strengthen, Durability, environment friendly and many of other. With this properties of concrete, sustainable concrete is an ideal substitute for ordinary concrete in the concrete industry. In the 21th century Machine learning is a tool which is use to employ the characteristics of sustainable concrete by using deep …
Published in Journal of Polymer & Composites · Vol. 12, Issue 7, 2024 · pp. 41–46 Read article
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Fusion of deep learning autoencoders with random forest for wetland classification using Sentinel-2A data: A case study on Sirpur wetland
Abstract: Present study analyses the performance of deep leaning algorithm-autoencoder to reduce data dimension as compared to conventional models. Classification accuracies of Sirpur wetland using Sentinel 2A dataset with different inputs have also been studied. These inputs sets comprise the reconstructed data through compression of original 13 bands into 4 bands using decoder algorithm, first four Principal Components, all spectral bands, and spectral indices. Random Forest classifier (RF) is used to …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 · pp. 25–35 Read article
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Loan Prediction Using Random Forest Algorithm
Abstract: With the growth of the banking sector, more and more people are applying for bank loans. All of these loans are not allowed. The principal income of bank assets arises from the interest earned on the loan. Bank profit or loss depends largely on the amount of the loan, i.e., whether customers pay off the loan or fail. The main purpose of banks is to invest their assets in secure …
Published in Journal of Advanced Database Management & Systems Read article
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DDoS Detection Using Cascade Correlation for Improving Network Resources in Cloud Environment
Abstract: Intrusion detection is critical for protecting network security from emerging cyber threats. This study describes a unique intrusion detection system (IDS) based on the Random Forest algorithm. Random Forests are used as an effective classifier to identify patterns linked with malevolent behaviour. This technique uses Random Forests to improve the accuracy and efficiency of intrusion detection systems. The suggested methodology's value is shown by its performance on the benchmark KDD …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 17–22 Read article
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Early Heart Disease Prediction Using Hybrid Machine Learning Techniques
Abstract: In the contemporary era, cardiovascular disease is one in all the most causes of death within the world. Estimating Heart problems i.e cardiopathy is a crucial challenge within the area of clinical data analysis. Large volumes of data produced by the healthcare sector have been proved to be useful for helping with decision-making and speculation, thanks to machine learning (ML).. Various studies help us to review and supply glimpse into …
Published in Journal of Microcontroller Engineering and Applications · Vol. 9, Issue 2, 2022 · pp. 35–41 Read article
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Climate Change Including Forest Fire Prediction using Machine Learning and Deep Learning
Abstract: Climate change alludes to long haul shifts in temperatures and atmospheric conditions. These movements might be regular, for example, through varieties in the sun-oriented cycle. In any case, since the 1800s, human exercises have been the fundamental driver of climate change, basically because of consuming fossil fuels like coal, oil and gas. Many individuals think climate change mostly implies hotter temperatures. Be that as it may, the temperature climb is …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 Read article
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Hand-Writing Recognition Using Structural, Statistical Features
Abstract: One of the very crucial challenges in pattern recognition operations is handwriting recognition, often known as handwritten number recognition. The processing of bank checks, the sorting of postal mail, the entry of data into forms, etc. are all procedures involving number recognition. The ability to create an efficient algorithm that can retrieve handwritten integers submitted by drug users via a scanner, tablet, and other digital gadgets is at the core …
Published in Journal of Electronic Design Technology · Vol. 14, Issue 1, 2023 · pp. 8–14 Read article
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Disease Prediction for Heart using Data Mining Techniques and Decision Tree Classification
Abstract: Heart disease is a prominent cause of death worldwide, and many people are concerned about it. Early detection of heart disease becomes very crucial and has the potential to save many lives. However, detecting cardiovascular diseases such as heart attacks, coronary artery disease, and others of similar types is a critical challenge presented by routine clinical data analysis, even by using well known algorithms. We can’t risk lives of people …
Published in Journal of Instrumentation Technology & Innovations · Vol. 12, Issue 2, 2022 · pp. 16–22 Read article
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AIS-based Anomaly Detection for IUU Fishing Activities
Abstract: The future of the Earth’s fish businesses is seriously threatened by the continuous use of illegal or illicit, unreported, and unregulated (IUU) fishing methods, a growing global demand, and deteriorating ocean ecosystem health. The livelihoods of legal fishing are also harmed by IUU fishing. The ongoing efforts to develop sustainable fisheries policies are also hampered by this. In order to manage fishery resources and ensure the safety of maritime traffic, …
Published in Current Trends in Information Technology · Vol. 13, Issue 1, 2023 · pp. 22–36 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 Prostate Cancer Using Boosting Technique
Abstract: There are many diseases that are associated with humans, but some diseases might be associated with only males or only females. This paper shows and discusses the disorder that is associated mainly in men. Prostate cancer is associated with the example of illness. Usually when the damaged cells develop in the prostate gland occurs prostate cancer occurs. These cells increase uncontrollably. Reports given by the researchers show that this is …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 3, 2023 · pp. 1–9 Read article
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Comparative Study of Classifiers for Monitoring Fake Reviews of Online Products Using Opinion Mining
Abstract: With the increasing popularity of e-commerce, online dealers seek reviews or opinions from customers regarding the quality and service of their sold products. As the number of customer reviews grows rapidly, potential buyers face difficulties in reading and assessing them to make informed decisions. Unfortunately, some review websites include fake positive reviews, either added by the product companies themselves or submitted by users who have not made a purchase. This …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 52–59 Read article
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Evaluation of Ensemble and Deep Learning Classifiers on CSE-CIC-IDS2018 Dataset for Intelligent NIDS
Abstract: Network Intrusion Detection System (NIDS) plays an active role in preventing cyberattacks by early detection of threats before it really starts affecting targeted information services. Over the years, many intrusion detection system (IDS) have been developed applying signature or rule-based approach to prevent unauthorised access of network or computer devices. However, ever growing landscape of cyberattacks in recent years has motivated present day researchers to design and develop more accurate …
Published in Current Trends in Information Technology · Vol. 13, Issue 1, 2023 · pp. 1–11 Read article