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440 articles for “Machine Learning”
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Research ArticleOpen accessIn the abstractA VF-IMF Cohesion Metric for Object-Oriented ClassesJoy Christy Antony Sami, Umamakeswari ArumugamCohesion in Object Oriented (OO) modules impact reusability, efficiency and complexity of software. OO Programmers are mandated to create software with high cohesion. The testing phase in Software Development Life Cycle (SDLC) is not only concerned about creating error free software but also assess quality of code through software metrics. The metric‘Lack of Cohesion in Methods (LCOM)’ is one of … …Journal of Computer Science, Vol. 16, Issue 4 · 10 Apr 2020 · 8,246 accessesView PDFCite
Research ArticleOpen accessIn the abstractEmail Spam Classification Using Gated Recurrent Unit and Long Short-Term MemoryIqbal Basyar, Adiwijaya, Danang Triantoro MurdiansyahHigh numbers of spam emails have led to an increase in email triage, causing losses amounting to USD 355 million per year. One way to reduce this loss is to classify spam email into categories including fraud or promotions made by unwanted parties. The initial development of spam email classification was based on simple methods such as word filters. Now, … …Journal of Computer Science, Vol. 16, Issue 4 · 3 Apr 2020 · 8,323 accessesView PDFCite
Research ArticleOpen accessIn the abstractDiagnosis of Hepatitis Disease with Logistic Regression and Artificial Neural NetworksAlaa M. Elsayad, Ahmed M. Nassef, Mujahed Al-DhaifallahHepatitis C refers to the inflammatory state of the liver caused by viruses, bacteria, fungi, and exposure to toxins such as alcohol and self-immunity. The diagnosis requires investigating many laboratory tests and comparing the results to those of the former patients with the same conditions. This study presents the results of our experiments to build a hybrid system that combines … …Journal of Computer Science, Vol. 16, Issue 3 · 27 Mar 2020 · 7,466 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 abstractFall Detection Using the Histogram of Oriented Gradients and Decision-Based FusionMohamed Maher Ben Ismail, Arwa AlGabas, Ouiem BchirAs the number of fall incidents among elderly people and patients are continuously growing, researches boosted their researches to propose efficient automatic fall detection systems. In particular, they formulated the fall detection problem as a supervised learning task where some visual features are extracted from the video frames and used to automatically identify the position of a human as “Fall” … …Journal of Computer Science, Vol. 16, Issue 2 · 26 Feb 2020 · 7,500 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 abstractComparison of Linear and Non-Linear Regression Models for Non-Invasive Blood Glucose MeasurementDorsaf Ghozzi, Yassine Manai, Khaled NouriThis paper deals with a new approach of non-invasive glucose monitoring based on near infrared spectroscopy. The proposed approach is coupled with a regression analysis in order to improve the predictive capacity of the designed device. Basic spectral data is a comparison that has been established between linear and non-linear machine learning regression algorithms. The experimental results show that feed … …Journal of Computer Science, Vol. 15, Issue 11 · 13 Nov 2019 · 7,864 accessesView PDFCite
Research ArticleOpen accessIn the abstractRandom Forest Based Feature Selection of Macroeconomic Variables for Stock Market PredictionIsaac Kofi Nti, Adebayo Felix Adekoya, Benjamin Asubam WeyoriA firm’s equity price on the stock-market is reported to be closely related to the Macroeconomic Variable (MVs) of the country in which the firm trades. For this reason, researchers, market traders, financial analysts and forecasters to examine the association between MVs and stock-price have carried out numerous studies, using time-series statistical analysis methods like Autoregressive Integrated Moving Average (ARIMA), … …American Journal of Applied Sciences, Vol. 16, Issue 7 · 31 Jul 2019 · 10,234 accessesView PDFCite
Review ArticleOpen accessIn the abstractWord Sense Disambiguation: Survey StudyAhmed H. Aliwy, Hawraa A. TaherThe process of identifying the correct sense of a given word in a particular sentence is called Word Sense Disambiguation (WSD). It is complex problem because it involves drawing knowledge from various sources. Significant amount of effort has been put into resolving this problem in machine learning since its inception but the toil is still ongoing. Many techniques were used … …Journal of Computer Science, Vol. 15, Issue 7 · 26 Jul 2019 · 8,388 accessesView PDFCite
Research ArticleOpen accessIn the abstractObject Detection and Classification from Thermal Images Using Region based Convolutional Neural NetworkUsha Mittal, Sonal Srivastava, Priyanka ChawlaIn recent years, object detection and classification has gained so much popularity in different application areas like face detection, self- driving cars, pedestrian detection, security surveillance systems etc. The traditional detection methods like background subtraction, Gaussian Mixture Model (GMM), Support Vector Machine (SVM) have certain drawbacks like overlapping of objects, distortion due to smoke, fog, lightening conditions etc. In this … …Journal of Computer Science, Vol. 15, Issue 7 · 18 Jul 2019 · 9,448 accessesView PDFCite