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 Conference Papers 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/. Title A name given to the resource Machine Learning Algorithms for Prediction of Mobile Phone Prices Subject The topic of the resource K-nearest neighbor; Machine learning; Mobile phone; Phone price prediction; Price range; Support vector machine Description An account of the resource The drastic growth of technology helps us to reduce the man work in our day-to-day life. Especially mobile technology has a vital role in all areas of our lives today. This work focused on a data-driven method to estimate the price of a new smartphone by utilizing historical data on smartphone pricing, and key feature sets to build a model. Our goal was to forecast the cost of the phone by using a dataset with 21 characteristics related to price prediction. Logistic regression (LR), decision tree (DT), support vector machine (SVM), Naive Bayes algorithm (NB), K-nearest neighbor (KNN) algorithm, XGBoost, and AdaBoost are only a few of the popular machine learning techniques used for the prediction. The support vector machine achieved the highest accuracy (97%) compared to the other four classifiers we tested. K-nearest neighbors 94% accuracy was close to that of the support vector machine. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Jose J.; Raj V.; Seaban S.V.; Jose D.V. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-537 LNNS, pp. 81-89. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-99-3010-4_7" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-99-3010-4_7</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174728762&amp;doi=10.1007%2F978-981-99-3010-4_7&amp;partnerID=40&amp;md5=92c871fadd4287c346b74af097ec0584" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174728762&amp;doi=10.1007%2f978-981-99-3010-4_7&amp;partnerID=40&amp;md5=92c871fadd4287c346b74af097ec0584</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981993009-8 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Jose J., Department of Computer Science, Rajagiri College of Social Sciences, Kalamassery, India; Raj V., Department of Computer Science, Rajagiri College of Social Sciences, Kalamassery, India; Seaban S.V., Department of Computer Science, Rajagiri College of Social Sciences, Kalamassery, India; Jose D.V., Department of Computer Science, Christ University, Bangalore, India