Results 1 to 10 of about 6,745,293 (217)
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Several machine-learning algorithms have been proposed for remote sensing image classification during the past two decades. Among these machine learning algorithms, Random Forest (RF) and Support Vector Machines (SVM) have drawn attention to image ...
M. Sheykhmousa +5 more
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Prediction of Heart Diseases using Random Forest
Journal of Physics: Conference Series, 2021 The process of discovering or mining information from a huge volume of data is known as data mining technology. Today data mining has lots of application in every aspects of human life. Applications of data mining are wide and diverse.
Madhumita Pal, S. Parija
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Three-Branch Random Forest Intrusion Detection Model
Mathematics, 2022 Network intrusion detection has the problems of large amounts of data, numerous attributes, and different levels of importance for each attribute in detection.
Chunying Zhang +4 more
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Journal of Thoracic Oncology, 2011 In the article by Chen et al,1 the authors used Random Survival Forests (RSF) as part of their approach for analyzing the data. In this note, we will explain RSF in a nontechnical way; precise details of the RSF method are described in the article by Ishwaran et al.2 RSF are an adaptation of Random Forests (RF)3 designed to be used for survival data ...
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Ransomware Detection using Random Forest Technique
ICT Express, 2020 Nowadays, the ransomware became a serious threat challenge the computing world that requires an immediate consideration to avoid financial and moral blackmail. So, there is a real need for a new method that can detect and stop this type of attack.
Ban Mohammed Khammas
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A comparison of random forest variable selection methods for classification prediction modeling
Expert systems with applications, 2019 Random forest classification is a popular machine learning method for developing prediction models in many research settings. Often in prediction modeling, a goal is to reduce the number of variables needed to obtain a prediction in order to reduce the ...
J. Speiser +3 more
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Unsupervised random forest for affinity estimation
Computational Visual Media, 2021 This paper presents an unsupervised clustering random-forest-based metric for affinity estimation in large and high-dimensional data. The criterion used for node splitting during forest construction can handle rank-deficiency when measuring cluster ...
Yunai Yi +5 more
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Archives of Medical Science, 2021 Introduction It is essential to predict the survival status of patients based on their prognosis. This can assist physicians in evaluating treatment decisions. Random forest is an excellent machine learning algorithm even without any modification.
Cheng Xu +4 more
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Computational and Structural Biotechnology Journal, 2022 Gene-to-gene networks, such as Gene Regulatory Networks (GRN) and Predictive Expression Networks (PEN) capture relationships between genes and are beneficial for use in downstream biological analyses.
Angelica M. Walker +7 more
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Prediction of COVID-19 confirmed, death, and cured cases in India using random forest model
Big Data Mining and Analytics, 2021 A novel coronavirus (SARS-CoV-2) is an unusual viral pneumonia in patients, first found in late December 2019, latter it declared a pandemic by World Health Organizations because of its fatal effects on public health In this present, cases of COVID-19 ...
V. Gupta +3 more
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