Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Haresh, Simon Mathew; Chalissery, Benita Jose; Newbegin, M. Title A name given to the resource Soft Voting Ensemble for Heart Disease Detection Using RF, CatBoost, and XGBoost Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Proceedings - 2025 International Conference on Transformative Computing Technologies, ICTCT 2025;pp.358-365 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICTCT69201.2025.00072" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICTCT69201.2025.00072</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105037444599?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105037444599?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Haresh S.M., Christ (Deemed to be) University, Department of Computer Science, Bangalore, India; Chalissery B.J., Christ (Deemed to be) University, Department of Computer Science, Bangalore, India; Newbegin M., Christ (Deemed to be) University, Department of Computer Science, Bangalore, India Description An account of the resource Global health reports constantly list heart disease as a major threat to human health. With the help of reliable information and early detection methods the disease's impact can be reduced. The study suggests an RCX(Random Forest, CatBoost, XGBoost) Ensemble machine learning method to figure out how likely a person is to get heart disease. Data for the system came through the UCI Repository containing records that were from Cleveland,Switzerland,Veterans Affairs(VA),Hungarian and statlog medical centers. As the raw datasets were not usable for performing operations, Data was put through preprocessing stages-which had involved removing missing values,making all labels uniform(standardizing them) and employing the SMOTE Technique for artificially creating new minority samples to balance the dataset. To explore an effective approach possible,models including Logistic Regression, Naive Bayes, Ran- dom Forest,CatBoost and gradient boosting(XGBoost) were trained and tested on the datasets. Using the Recursive Feature Elimination (RFE) method 8 out of 14 relevant features were selected. The models were improved through hyperparameter tuning and Among all models used the best results had come from a soft voting ensemble that combined Random Forest, CatBoost and XGBoost. The RCX ensemble model which was developed, has been shown to give accuracy and ROC AUC results of 91.18% and 96.21% respectively, showing stronger results compared to individual models. Metrics and Indicators like accuracy, precision, recall, F1-Score and the ROC AUC were used for comparing performance during testing periods. The data was visualized by using Python libraries such as matplotlib and seaborn for confusion matrices, heatmaps,and bar graphs for better understanding of the data at a glance. 2025 IEEE. Subject The topic of the resource Ensemble Learning; Heart Disease; Machine Learning; RCX Ensemble; SMOTE; Soft Voting Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833159195-3; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online