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114 results for “Decision Tree”
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Research ArticleOpen accessIn the abstractDevelopment and Implementation of the HACCP System on the Production Line of Kefir from Goat's MilkGaukhar Yussupova, Dina Kurmangaliyeva, Zhazira Shadyarova et al.The purpose of this work is to develop a HACCP plan with the subsequent implementation of the HACCP system to ensure the safety of production of kefir from goat's milk produced in the "Breeding farm" Zerenda "LLP in the Akmola region. When implementing HACCP defined policy and security of products, the scope of the HACCP system, the appointment of working … …OnLine Journal of Biological Sciences, Vol. 20, Issue 3 · 9 Oct 2020 · 8,366 accessesView PDFCite
Research ArticleOpen accessIn the abstractResearch on the Link Between Economic Development Variables and the Rate of Access to Drinking Water in Rural Senegal Using Machine LearningAnabilaye Moussa Coly, Alioune Ly, Ndolane Diouf et al.After pre-processing a set of data collected from Senegalese state structures, official United Nations (UN), and world bank sites and after replacing missing values by interpolation using the mean between two values, we study the effect of macroeconomic development variables on the rate of access to drinking water in rural Senegal. To do this, we use Machine Learning (ML) techniques … …American Journal of Applied Sciences, Vol. 20, Issue 1 · 20 Dec 2023 · 6,208 accessesView PDFCite
Research ArticleOpen accessIn the abstractHuman Age Predication from Face Images Based on Combining Deep Wavelet Network and Machine Learning AlgorithmsZahraa Salam Abu Ghrban, Nidhal K. EL AbbadiDue to the numerous variances in face appearance, age estimation using facial images is a difficult subject. Many factors can affect the estimation of human age such as race, face post, gender, lifestyle, etc. By considering more factors, the optimum performance may be obtained. In this study, we proposed a method to predict the age of facial images. The proposed … …Journal of Computer Science, Vol. 19, Issue 5 · 5 May 2023 · 5,573 accessesView PDFCite
Research ArticleOpen accessIn the abstractBreast Cancer Grading using Machine Learning Approach AlgorithmsHiba Nabeel Zalloum, Saada Al Zeer, Amir Manassra et al.Recently, Breast Cancer (BC) becomes a more common cancer disease in women and it considers the most important sign which leads to death among women. Therefore, it requires efficient methods for detecting it to reduce the risk of death. A positive prognosis and greater chances of survival are improved if the BC is detected early. Currently, machine learning plays an … …Journal of Computer Science, Vol. 18, Issue 12 · 22 Dec 2022 · 6,619 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetection of Rust Emergence in Coffee Plantations using Data Mining: A Systematic ReviewLenin Quiñones Huatangari, Candy Lisbeth Ocaña Zúñiga, Annick Estefany Huaccha Castillo et al.Hemileia vastatrix is a fungus that causes coffee rust disease and, depending on the level of severity, reduces the photosynthetic capacity of the plant and of new shoots, leading to low coffee yields and even death; its symptoms are visible on the leaf. Systems based on computer algorithms have been developed to predict diseases and pests in coffee. The objective … …OnLine Journal of Biological Sciences, Vol. 22, Issue 2 · 31 Mar 2022 · 8,028 accessesView PDFCite
Research ArticleOpen accessIn the abstractMachine Learning and Deep Learning for Phishing Email Classification using One-Hot EncodingSikha Bagui, Debarghya Nandi, Subhash Bagui, Robert Jamie WhiteRepresentation of text is a significant task in Natural Language Processing (NLP) and in recent years Deep Learning (DL) and Machine Learning (ML) have been widely used in various NLP tasks like topic classification, sentiment analysis and language translation. Until very recently, little work has been devoted to semantic analysis in phishing detection or phishing email detection. The novelty of … …Journal of Computer Science, Vol. 17, Issue 7 · 23 Jul 2021 · 10,940 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Performance of Supervised Learning Algorithms for Flood Prediction in Kemaman, TerengganuNur Najihah Shaaban, Norlida Hassan, Aida Mustapha, Salama A. MostafaFlood is one of the most destructive phenomena all over the world. Because the flooding uncertainties and the urgency to prepare for disaster management, three specific technique approaches are compared in this study to predict the flood occurrence based on historical rainfall data. The study involved the rainfall data in Kemaman, Terengganu between 2017 and 2018 extracted from the official … …Journal of Computer Science, Vol. 17, Issue 5 · 7 May 2021 · 6,892 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntegrated Multiple Linear Regression-One Rule Classification Model for the Prediction of Stock Price TrendLock Siew Han, Md Jan NordinOne of the main problems of predicting stock price with regression approach is overfitting a model. An overfit model becomes tailored to fit the random noise in the dataset rather than reflecting the overall population. For this it is necessary to construct an integrated regression-classification model to approximate the true model for the entire population in the dataset. The proposed … …Journal of Computer Science, Vol. 13, Issue 9 · 18 May 2017 · 7,428 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Integrated Machine Learning Model for Heart Disease Classification and CategorizationSrikanth Meda, Raveendrababu BhogapathiProgressions in the coordination among the machine learning algorithms, helped to achieve high accuracy and reliability in decision-making systems. Due to the impact and importance of heart diseases in real life, designing the efficient heart disease prediction model become a pivotal aspect today. Former research scholars applied the popular supervised machine learning models like Decision Trees, Naïve Bayes, ANN's, and … …Journal of Computer Science, Vol. 18, Issue 4 · 19 Apr 2022 · 6,539 accessesView PDFCite
Research ArticleOpen accessIn the abstractPhonocardiogram Classification Based on Machine Learning with Multiple Sound FeaturesKhalid M.O. Nahar, Obaida M. Al-Hazaimeh, Ashraf Abu-Ein, Nasr GharaibehIn this study the heartbeat sound signals were tackled by classifying them into heart disease categories such as normal, artifact, murmur and extrahals in an attempt for early detection of heart defects. Phonocardiogram (i.e., PCG) is used to obtain the digital recording dataset of the heart sounds using an electronic stethoscope or mobile device. Multiple features are extracted from the … …Journal of Computer Science, Vol. 16, Issue 11 · 26 Nov 2020 · 8,263 accessesView PDFCite