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In order to improve the effectiveness of SMOTE, this paper presents a novel over-sampling method using codebooks obtained by the learning vector quantization.
In order to tackle this problem, we have proposed to generate synthetic samples using codebooks obtained by the learning vector quantization.
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As a solution to the problem, this paper presents a novel over-sampling method using codebooks obtained by LVQ (Learning Vector Quantization) [ 11].
This paper has presented a new over-sampling method using codebooks obtained by Learning Vector Quantization.
Er, Yumusak and Temurtas [ 18] presented a comparative chest diagnosis; for chronic obstructive pulmonary, pneumonia, asthma, tuberculosis and lung cancer diseases which was realized by using multilayer, probabilistic, learning vector optimization, and generalized regression.
The fault diagnosis of planetary gear is eventually realized by applying the extracted kernel principal components and learning vector quantization (LVQ) neural network.
Kohonen learning vector quantization.
First, the nonlinear process with measurement noise is regressed by the relevance vector learning mechanism based on a kernel-based Bayesian framework.
The last few years have seen great steps forward in particular types of machine learning: vector-based machine learning and deep learning.
The prediction model was learned by the support vector regression (SVR) algorithm.
The basic idea is to launch cooperative monitoring between vehicles to build a training dataset that is analyzed by the Support Vector Machine (SVM) learning technique in online and incremental fashions to classify the smart vehicles either cooperative or malicious.
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