Results 51 to 60 of about 537,050 (171)
A Review of Space Target Recognition Based on Ensemble Learning
AerospaceThe increasing number of space debris and space-active targets makes the space environment more and more complex. Space target recognition, a crucial component of space situational awareness, is of paramount importance to space security.
Shiyan Wang +3 more
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IEEE Access, 2022 The ensemble learning method is a necessary process that provides robustness and is more accurate than the single model. The snapshot ensemble convolutional neural network (CNN) has been successful and widely used in many domains, such as image ...
Sangdaow Noppitak, Olarik Surinta
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Online Ensemble Learning of Sensorimotor Contingencies [PDF]
, 2015 Forward models play a key role in cognitive agents by providing predictions of the sensory consequences of motor commands, also known as sensorimotor contingencies (SMCs). In continuously evolving environments, the ability to anticipate is fundamental in
Demiris, Y, Zambelli, M
core
Ensembles of Learning Machines [PDF]
, 2002 Ensembles of learning machines constitute one of the main current directions in machine learning research, and have been applied to a wide range of real problems. Despite of the absence of an unified theory on ensembles, there are many theoretical reasons for combining multiple learners, and an empirical evidence of the effectiveness of this approach ...
G. VALENTINI, MASULLI, FRANCESCO
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A Python code smell detection method based on ensemble learning
上海师范大学学报. 自然科学版A Python code odor detection method based on ensemble learning was proposed in this paper, which was used to detect five types of code smell. Two ensemble learning methods, stacked ensemble and voting ensemble, were adopted to detect code smell, and ...
CAO Yue, CHEN Junhua
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Complementary Ensemble Learning
, 2021 To achieve high performance of a machine learning (ML) task, a deep learning-based model must implicitly capture the entire distribution from data. Thus, it requires a huge amount of training samples, and data are expected to fully present the real distribution, especially for high dimensional data, e.g., images, videos.
Nguyen, Hung, Chang, Morris
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Pycobra: A Python Toolbox for Ensemble Learning and Visualisation [PDF]
, 2018 We introduce \texttt{pycobra}, a Python library devoted to ensemble learning (regression and classification) and visualisation. Its main assets are the implementation of several ensemble learning algorithms, a flexible and generic interface to compare ...
Desikan, Bhargav Srinivasa +1 more
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A framework for detecting credit card fraud with cost-sensitive meta-learning ensemble approach
Scientific African, 2020 Electronic payment systems continue to seamlessly aid business transactions across the world, and credit cards have emerged as a means of making payments in E-payment systems. Fraud due to credit card usage has, however, remained a major global threat to
Toluwase Ayobami Olowookere +1 more
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An Effective Ensemble Approach for Preventing and Detecting Phishing Attacks in Textual Form
Future InternetPhishing email assaults have been a prevalent cybercriminal tactic for many decades. Various detectors have been suggested over time that rely on textual information.
Zaher Salah +5 more
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Prediction and Analysis of Rice Production and Yields Using Ensemble Learning Techniques
Ilkom Jurnal IlmiahThis research focuses on predicting and analyzing rice production and yield throughout the world using ensemble learning techniques. The study applies and compares three methods: linear regression, ARIMA, and ensemble learning, to predict rice harvest ...
Yudha Islami Sulistya +6 more
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