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Machine vector mutation This first operator uses a random selection of an index from the machine vector MA.
The support machine vector is applied to analyze the differences between the SERS data and discriminate the patients from healthy subjects.
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45 In another study, a support machine vector-based method is used for the identification of lipocalin protein sequences with high predictive accuracy (>90% in leave-one-out).
As a kind of machine-learning methods, Support Vector Machine has the potential to solve this complex issue.
The last few years have seen great steps forward in particular types of machine learning: vector-based machine learning and deep learning.
In 2001 Tipping [24] elaborated a new support vector machine, called Relevance Vector Machine (RVM), merging the Vapnik theory with the Bayesian statistics.
Support vector machine is a supervised machine learning technique used for classification and regression analysis [ 29].
In this study, SVM (Support Vector Machine) was applied for machine learning approach [ 58].
Support vector machine (SVM) is a machine learning algorithm mainly used for the purpose of classification.
We make a comparison of our proposed mSVDD with ball vector machine (BVM) [22], core vector machine (CVM) [23] and support vector data description (SVDD) [21].
Support vector machine was the best performing machine learning method using clinical, genetic or both attributes.
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