Results 31 to 40 of about 427,183 (276)
Coupled Least Squares Support Vector Ensemble Machines
Information, 2019 The least squares support vector method is a popular data-driven modeling method which shows better performance and has been successfully applied in a wide range of applications.
Dickson Keddy Wornyo, Xiang-Jun Shen
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Damage Diagnosis of Bolt Loosening via Vector Autoregressive - Support Vector Machines
Hittite Journal of Science and Engineering, 2020 Developments in engineering techniques have concentrated on how to build better solutions for engineering structures in order to main the integrity and to reduce the costs in operations.
Mahmut Pekedis
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The Stata Journal: Promoting communications on statistics and Stata, 2016 Support vector machines are statistical- and machine-learning techniques with the primary goal of prediction. They can be applied to continuous, binary, and categorical outcomes analogous to Gaussian, logistic, and multinomial regression. We introduce a new command for this purpose, svmachines.
Nick Guenther, Matthias Schonlau
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Explaining Support Vector Machines: A Color Based Nomogram. [PDF]
PLoS ONE, 2016 PROBLEM SETTING:Support vector machines (SVMs) are very popular tools for classification, regression and other problems. Due to the large choice of kernels they can be applied with, a large variety of data can be analysed using these tools.
Vanya Van Belle +4 more
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The ubiquitin ligase RNF115 is required for the clearance of damaged lysosomes
FEBS Letters, EarlyView.Upon lysosomal rupture, an E3 ubiquitin ligase RNF115 translocates from the cytosol to the damaged lysosomal membrane. Moreover, RNF115 depletion impairs the clearance of damaged lysosomes, identifying it as a key regulator of lysosomal quality control.
Sae Nakanaga +3 more
wiley +1 more source
Twin Bounded Weighted Relaxed Support Vector Machines
IEEE Access, 2019 Data distribution has an important role in classification. The problem of imbalanced data has occurred when the distribution of one class, which usually attends more interest, is negligible compared with other class.
Fatemeh Alamdar +2 more
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Molecular Oncology, EarlyView.Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova +25 more
wiley +1 more source
Recent advances on support vector machines research
Technological and Economic Development of Economy, 2012 Support vector machines (SVMs), with their roots in Statistical Learning Theory (SLT) and optimization methods, have become powerful tools for problem solution in machine learning.
Yingjie Tian, Yong Shi, Xiaohui Liu
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Molecular Oncology, EarlyView.Tumors contain diverse cellular states whose behavior is shaped by context‐dependent gene coordination. By comparing gene–gene relationships across biological contexts, we identify adaptive transcriptional modules that reorganize into distinct vulnerability axes.
Brian Nelson +9 more
wiley +1 more source
Random Projections for Linear Support Vector Machines
, 2014 Let X be a data matrix of rank \rho, whose rows represent n points in d-dimensional space. The linear support vector machine constructs a hyperplane separator that maximizes the 1-norm soft margin. We develop a new oblivious dimension reduction technique
Boutsidis, Christos +3 more
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