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49 results for “Machine Learning Classifiers”
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Research ArticleOpen accessIn the abstractClassification Algorithm in Predicting the Diabetes in Early StagesSubitha Sivakumar, Sivakumar Venkataraman, Asherl BwatirambaDiabetes is a standout amongst the deadliest and Chronical diseases which can increase the blood sugar in the human body. Diabetes gives several complications if it is not diagnosed and treated where it might lead to lifeless. Diabetes could be actively controlled when it is primary predicted. To solve this problem and to predict the diabetes in early stage, the … …Journal of Computer Science, Vol. 16, Issue 10 · 24 Oct 2020 · 7,069 accessesView PDFCite
Research ArticleOpen accessIn the abstractStudy and Analysis of Prediction Model for Heart Disease Data Using Machine Learning TechniquesB. Santhi, K. RenukaHeart disease is the number one cause of death for all communities of individuals in advanced countries and a major problem for emerging nations too. Doctors’ availability to care for the general population could not catch up with the present demand for healthcare. So, there is a severe need for a support system to assist save individuals. With novel ML … …Journal of Computer Science, Vol. 16, Issue 3 · 26 Mar 2020 · 7,784 accessesView PDFCite
Research ArticleOpen accessIn the abstractMissing Values Treatment and Feature Reduction Analysis to Enhance ClassificationD. Muralidharan, K. Renuka, Mulagala Jaswant et al.Datasets may have large number of features which makes it hard and time consuming to classify. Additionally, they may have irrelevant and noise features too with missing values. The missing values should be treated in a proper way so that the classifier accuracy can be improved. There is also a need to reduce features and select only the features necessary … …Journal of Computer Science, Vol. 16, Issue 2 · 20 Feb 2020 · 8,114 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluation of Classification Models for Predicting Mortality Rate Using Thyroid Cancer DataNorah Saleh AlghamdiMachine Learning (ML) can potentially enhance predictions in real-life domains. This study presents an evaluation and comparison of different ML methods which can be applied on thyroid cancer dataset, called Prostate, Lung, Colorectal and Ovarian (PLCO), of approximately 155,000 participants with thyroid cancer occurrence and mortality incidence. The ML models are explored for predicting mortality rates of patients with thyroid … …Journal of Computer Science, Vol. 15, Issue 1 · 21 Jan 2019 · 7,788 accessesView PDFCite
Research ArticleOpen accessIn the abstractSentiment Analysis of French Tweets based on Subjective Lexicon Approach: Evaluation of the use of OpenNLP and CoreNLP ToolsAbdelkader Rhouati, Jamal Berrich, Mohammed G. Belkasmi, Toumi BouchentoufNowadays, sentiment analysis is becoming a very important issue of research. This paper present experimentation on sentiment analysis based on subjective lexicon method. This experimentation is tested over French tweets using "Public Opinion Knowledge (POK)" platform. POK is a platform consists in getting public opinion orientation from text extracted from social network and blogs, which we have developed and presented … …Journal of Computer Science, Vol. 14, Issue 6 · 25 Jun 2018 · 8,339 accessesView PDFCite
Research ArticleOpen accessIn the abstractUnfair Reviews Detection on Amazon Reviews using Sentiment Analysis with Supervised Learning TechniquesElshrif Ibrahim Elmurngi, Abdelouahed GherbiReputation and trust are significantly important and play a pivotal role in enabling multiple parties to establish relationships that achieve mutual benefit especially in an E-Commerce (EC) environment. There are several factors negatively affecting the sight of customers and sellers in terms of reputation. For instance, lack of credibility in providing feedback reviews, by which users might create phantom feedback … …Journal of Computer Science, Vol. 14, Issue 5 · 14 May 2018 · 9,882 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassification of Breast Tumor in Mammogram Images Using Unsupervised Feature LearningAidarus M. Ibrahim, Baharum Baharudin, Abas Md Said, P. N. HashimahIn this study, we propose a learning-based approach using feature learning to minimize the manual effort required to extract features. Firstly, we extracted features from equally spaced sub-patches covering the input Region of Interest (ROI). The dimensionality of the extracted features is reduced using max-pooling. Furthermore, spherical k-means clustering coupled with max pooling (k-means-max pooling) is compared with well-known feature … …American Journal of Applied Sciences, Vol. 13, Issue 5 · 13 May 2016 · 7,497 accessesView PDFCite
Research ArticleOpen accessIn the abstractDiagnosis of Cardiovascular Diseases with Bayesian ClassifiersAlaa Elsayad, Mahmoud FakhrCardiovascular disease or atherosclerosis is any disease affecting the cardiovascular system. They include coronary heart disease, raised blood pressure, cerebrovascular disease, peripheral artery disease, rheumatic heart disease, congenital heart disease and heart failure. They are treated by cardiologists, thoracic surgeons, vascular surgeons, neurologists and interventional radiologists. The diagnosis is an important yet complicated task that needs to be done accurately … …Journal of Computer Science, Vol. 11, Issue 2 · 25 Mar 2015 · 7,498 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Evaluation of Phone Duration Models for Greek Emotional SpeechAlexandros Lazaridis, Vasiliki Bourna, Nikos FakotakisProblem statement: In this study we cope with the task of phone duration modeling for Greek emotional speech synthesis. Approach: Various well established machine learning techniques are applied for this purpose to an emotional speech database consisting of five archetypal emotions. The constructed phone duration prediction models are built on phonetic, morphosyntactic and prosodic features that can be extracted only … …Journal of Computer Science, Vol. 6, Issue 3 · 31 Mar 2010 · 7,065 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordToward Intelligent Evaluation of Digital Public Services: Evidence from Indonesia’s SIM Online PlatformEvaristus Didik Madyatmadja, Ricky Kosasih, Najla Aurelia Evanthe et al.This investigation examines more than 65,000 user evaluations from the Google Play Store concerning sentiment toward the Digital Korlantas POLRI application. Reviews were systematically processed and categorized through Naïve Bayes, Support Vector Machine, and Random Forest classifiers, thereby highlighting the perceived strengths and weaknesses of the platform. Among the tested models, Naïve Bayes outperformed the others, yielding the greatest accuracy, … …Journal of Computer Science, Vol. 22, Issue 6 · 15 Jun 2026 · 1,345 accessesView PDFCite