Results 21 to 30 of about 9,169,616 (322)
Parallel Support Vector Machine Algorithm Based on Clustering and WOA [PDF]
Jisuanji kexue, 2022 Aiming at the problems of parallel support vector machine(SVM) being sensitive to redundant data,poor parameter optimization ability and load imbalance in parallel process in the big data environment,a parallel support vector machine algorithm—MR-KWSVM ...
LIU Wei-ming, AN Ran, MAO Yi-min
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Transport, 2011 A support vector machine is a machine learning method based on the statistical learning theory and structural risk minimization. The support vector machine is a much better method than ever, because it may solve some actual problems in small samples ...
Yanrong Hu, Chong Wu, Hongjiu Liu
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Complexity, 2021 The safety problem of the slope has always been an important subject in engineering geology, which has a wide range of application background and practical significance in reality.
Fei Li, Hongyun Zhang
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Analisis Sentimen Tweet Tentang UU Cipta Kerja Menggunakan Algoritma SVM Berbasis PSO
JISKA (Jurnal Informatika Sunan Kalijaga), 2022 Support Vector Machine (SVM) is one of the most widely used classification algorithms for sentiment analysis and has been shown to provide satisfactory performance.
Trifebi Shina Sabrila +2 more
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Support Vector Machines (SVM) as a Technique for Solvency Analysis [PDF]
SSRN Electronic Journal, 2008 This paper introduces a statistical technique, Support Vector Machines (SVM), which is considered by the Deutsche Bundesbank as an alternative for company rating. A special attention is paid to the features of the SVM which provide a higher accuracy of company classification into solvent and insolvent. The advantages and disadvantages of the method are
Laura Auria, Rouslan A. Moro
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Support Vector Machines in R [PDF]
, 2005 Being among the most popular and efficient classification and regression methods currently available, implementations of support vector machines exist in almost every popular programming language.
Kurt Hornik +5 more
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Support Vector Machine (SVM) for Colorization the Grayscale Image
Al-Qadisiyah Journal for Engineering Science, 2020 Recently, there have been several automatic approaches to color grayscale images, which depend on the internal features of the grayscale images. There are several scales which are considered as a prominent key to extract the corresponding chromatic value
Shymaa Akram Alrubaie a +1 more
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Multitraining support vector machine for image retrieval [PDF]
, 2006 Relevance feedback (RF) schemes based on support vector machines (SVMs) have been widely used in content-based image retrieval (CBIR). However, the performance of SVM-based RF approaches is often poor when the number of labeled feedback samples is small.
Tao, D. +7 more
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Robust ASR using Support Vector Machines [PDF]
, 2007 The improved theoretical properties of Support Vector Machines with respect to other machine learning alternatives due to their max-margin training paradigm have led us to suggest them as a good technique for robust speech recognition. However, important
F. Díaz-de-María +17 more
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Vector machine techniques for modeling of seismic liquefaction data
Ain Shams Engineering Journal, 2014 This article employs three soft computing techniques, Support Vector Machine (SVM); Least Square Support Vector Machine (LSSVM) and Relevance Vector Machine (RVM), for prediction of liquefaction susceptibility of soil.
Pijush Samui
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