机器学习7-SVM

最新推荐文章于 2022-09-23 19:44:55 发布

Diehard_Yin

最新推荐文章于 2022-09-23 19:44:55 发布

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分类专栏：机器学习文章标签：机器学习 svm

本文链接：https://blog.youkuaiyun.com/yinlili2010/article/details/41419141

本文探讨了在特征较多和大规模训练集的情况下，如何应对欠拟合问题。作者建议使用神经网络和带高斯核的支持向量机来解决这一挑战。文章通过五个问题逐步展开讨论，总结中强调了这两种方法的有效性。

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Question 1

Suppose you have trained an SVM classifier with a Gaussian kernel, and it learned the following decision boundary on the training set:
SVM result with underfit decision boundary

SVM result with underfit decision boundary

You suspect that the SVM is underfitting (==high bais)your dataset. Should you try increasing or decreasing

C? Increasing or decreasing

σ2?

Your Answer		Score	Explanation
It would be reasonable to try decreasing C. It would also be reasonable to try decreasing σ2.
It would be reasonable to try increasing C. It would also be reasonable to try decreasing σ2.	Correct	1.00	The figure shows a decision boundary that is underfit to the training set, so we'd like to lower the bias / increase the variance of the SVM. We can do so by either increasing the parameter C or decreasing σ2.
It would be reasonable to try increasing C. It would also be reasonable to try increasing σ2.
It would be reasonable to try decreasing C. It would also be reasonable to try increasing σ2.
Total		1.00 / 1.00