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81 articles for “Applied Machine Learning”
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Research ArticleOpen accessIn the abstractA Collaborative Prediction of Presence of Arrhythmia in Human Heart with Electrocardiogram Data using Machine Learning Algorithms with AnalyticsSelvaraj Rajalakshmi, Kuthadi Venu MadhavHuman heart is the major organ of human being which could fail the other systems in the body at the same time. Hence predicting heart disease is one of the challenging researches that requires meticulous analysis of heart rhythms properly. The irregular heart rhythms or beat is referred to as the Arrhythmia where heart rhythms with low or high rates … …Journal of Computer Science, Vol. 15, Issue 2 · 22 Feb 2019 · 7,508 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 abstractA Survey on Recent Applications of Machine Learning with Big Data in Additive Manufacturing IndustryMicheal Omotayo Alabi, Ken Nixon, Ionel BotefAdditive Manufacturing (AM) which is also known as 3D printing technology; is recognized as a new paradigm for manufacturing industry. Additive manufacturing is rapidly expanding across different sectors such as healthcare, electronics, automotive, science and engineering, education, dental, etc. Machine Learning and Big Data are both emerging technologies which are becoming popular and gaining more attention from the industries and … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 3 · 14 Jul 2018 · 10,279 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Enhanced Training- Based Arabic Sign Language Virtual Interpreter Using Parallel Recurrent Neural NetworksMohamed A. AbdouIntelligent machine translation systems have a remarkable importance in integrating people with disabilities in community. Arabic to Arabic sign language systems are limited. Deep Learning (DL) was successfully applied to problems related to music information retrieval, image recognition and text recognition, but its use in sign language recognition is rare. This paper introduces an automatic virtual translation system from Arabic … …Journal of Computer Science, Vol. 14, Issue 2 · 20 Feb 2018 · 7,628 accessesView PDFCite
Research ArticleOpen accessIn the abstractLandslide Susceptibility Analysis Using Numerical and Neural Network, Near Kedarnath, Uttarakhand, IndiaVinay Kumar Singh, Tariq Anwar Ansari, Vikram Vishal, T.N. SinghThe major concern in hilly regions is the stability of those slopes, which have been proclaimed due to unplanned excavation and uneven blasting during road widening and development activity. These slopes again become more vulnerable under dynamic loading and/or various types of human involvement, heavy rainfall and seismic activity. Failure of these slopes leads to loss of property and human … …American Journal of Environmental Sciences, Vol. 16, Issue 1 · 9 Mar 2020 · 7,772 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 abstractArabic Static and Dynamic Gestures Recognition Using Leap MotionBasma Hisham, Alaa HamoudaAcross the world, several millions of people use sign language as their main way of communication with their society, daily they face a lot of obstacles with their families, teachers, neighbours, employers. According to the most recent statistics of World Health Organization, there are 360 million persons in the world with disabling hearing loss i.e. (5.3% of the world’s population), … …Journal of Computer Science, Vol. 13, Issue 8 · 12 Aug 2017 · 8,178 accessesView PDFCite
Research ArticleOpen accessIn the abstractRandom Forest Classification and Support Vector Machine for Detecting Epilepsyusing Electroencephalograph RecordsHeri Kuswanto, Mutiah Salamah, Muhammad Idrus FachruddinComplexity in data structure has led to the rapid development of computational statistics methods. Machine learning approaches have been introduced and applied to solve complex problems in many fields. This paper applies two common machine learning approaches, Random Forest (RF) and Support Vector Machine (SVM), in the detection of epilepsy. The diagnosis of epilepsy can usually only be made when … …American Journal of Applied Sciences, Vol. 14, Issue 5 · 4 May 2017 · 8,134 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Approach to Pronominal Anaphora Resolution in ArabicAbdullatif Abolohom, Nazlia OmarOne of the challenges in natural language processing is to determine which pronouns to be referred to their intended referents in the discourse. Performing anaphora resolution is considered as an important task for a number of natural language processing applications such as information extraction, question answering and text summarization. Most of the earlier works of anaphora resolution have been applied … …Journal of Computer Science, Vol. 11, Issue 5 · 17 Aug 2015 · 7,092 accessesView PDFCite
Research ArticleOpen accessIn the abstractA New Cooperative Algorithm Based on PSO and K-Means for Data ClusteringMehdi Neshat, Shima Farshchian Yazdi, Daneyal Yazdani, Mehdi SargolzaeiProblem statement: Data clustering has been applied in multiple fields such as machine learning, data mining, wireless sensor networks and pattern recognition. One of the most famous clustering approaches is K-means which effectively has been used in many clustering problems, but this algorithm has some drawbacks such as local optimal convergence and sensitivity to initial points. Approach: Particle Swarm Optimization … …Journal of Computer Science, Vol. 8, Issue 2 · 19 Nov 2011 · 7,967 accessesView PDFCite