支持向量机是继神经网络后机器学习的热点研究技术，它主要应用于分类和回归问题中。

SVM is the hot issue accompanying artificial neural network in machine learning. It involves any practical problems such as classification and regression estimation.

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它不仅有助于科学家对机器学习和神经计算的深入研究，还有助于普通工程技术人员利用神经网络技术来解决真实世界中的问题。

It is not only helpful for scientists to investigate machine learning and neural computing but also helpful for common engineers to solve real world problems using neural network techniques.

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同时本文将机器学习和相关反馈结合起来用于图像检索，在实验中使用了K - NN、BP神经网络和支持向量机分类器。

At the same time, we used relevance feedback and machine learning used in image retrieval. K-NN, BP neural network and support vector machine classifiers were used in experiments.

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