This study explores the impact of hyperparameter optimization on machine learning models for predicting cardiovascular disease using data from an IoST(Internet of Sensing Things)*** distinct machine learning approache...
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This study explores the impact of hyperparameter optimization on machine learning models for predicting cardiovascular disease using data from an IoST(Internet of Sensing Things)*** distinct machine learning approaches were implemented and systematically evaluated before and after hyperparameter *** improvements were observed across various models,with SVM and Neural Networks consistently showing enhanced performance metrics such as F1-Score,recall,and *** study underscores the critical role of tailored hyperparameter tuning in optimizing these models,revealing diverse outcomes among *** Trees and Random Forests exhibited stable performance throughout the *** enhancing accuracy,hyperparameter optimization also led to increased execution *** representations and comprehensive results support the findings,confirming the hypothesis that optimizing parameters can effectively enhance predictive capabilities in cardiovascular *** research contributes to advancing the understanding and application of machine learning in healthcare,particularly in improving predictive accuracy for cardiovascular disease management and intervention strategies.
The term sentiment analysis deals with sentiment classification based on the review made by the user in a social *** sentiment classification accuracy is evaluated using various selection methods,especially those that d...
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The term sentiment analysis deals with sentiment classification based on the review made by the user in a social *** sentiment classification accuracy is evaluated using various selection methods,especially those that deal with algorithm *** this work,every sentiment received through user expressions is ranked in order to categorise sentiments as informative and *** order to do so,the work focus on Query Expansion Ranking(QER)algorithm that takes user text as input and process for sentiment analysis andfinally produces the results as informative or *** challenge is to convert non-informative into informative using the concepts of classifiers like Bayes multinomial,entropy modelling along with the traditional sentimental analysis algorithm like Support Vector Machine(SVM)and decision *** work also addresses simulated annealing along with QER to classify data based on sentiment *** the input volume is very fast,the work also addresses the concept of big data for information retrieval and *** result com-parison shows that the QER algorithm proved to be versatile when compared with the result of *** work uses Twitter user comments for evaluating senti-ment analysis.
Early and accurate detection of breast cancer, particularly Invasive Ductal Carcinoma (IDC), is critical for improving patient outcomes. Traditional diagnostic methods like histopathology and mammography have limitati...
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The event management mechanism matches messages that have been subscribed to and events that have been published. To identify the subscriptions that correspond to the occurrence inside the category, it must first run ...
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In the wake of rapid advancements in artificial intelligence(AI), we stand on the brink of a transformative leap in data systems. The imminent fusion of AI and DB(AI×DB) promises a new generation of data systems,...
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In the wake of rapid advancements in artificial intelligence(AI), we stand on the brink of a transformative leap in data systems. The imminent fusion of AI and DB(AI×DB) promises a new generation of data systems, which will relieve the burden on end-users across all industry sectors by featuring AI-enhanced functionalities, such as personalized and automated in-database AI-powered analytics, and selfdriving capabilities for improved system performance. In this paper, we explore the evolution of data systems with a focus on deepening the fusion of AI and DB. We present NeurDB, an AI-powered autonomous data system designed to fully embrace AI design in each major system component and provide in-database AI-powered analytics. We outline the conceptual and architectural overview of NeurDB, discuss its design choices and key components, and report its current development and future plan.
The Intelligent Surveillance Support System(ISSS) is an innovative software solution that enables real-time monitoring and analysis of security footage to detect and identify potential threats. This system incorporate...
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Providing students with a top-notch education is the main goal of educational establishments. This study intends to use a variety of data mining tools in order to evaluate their effectiveness and determine the impact ...
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Birds are nice-looking from their aesthetic looks and life styles, around 50 billion of birds are living on the earth where some birds are in threat of extinction. For people, distinguishing and classification of bird...
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The Internet of Things (IoT) becomes the most demanding technology over the past few years. IoT is the basic need of daily life. The security of these devices is very important because they contain large files of sens...
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Agriculture as the cornerstone of food production, involves key phases like crop cultivation and animal breeding. Beyond sustenance, agriculture significantly contributes to pharmaceutical industries by producing medi...
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