使用在Matlab中训练的SVM模型在python中进行分类

Question

I have a SVM model trained in MATLAB (using 6 features) for which I have:

• Support Vectors [337 x 6]
• Alpha [337 x 1]
• Bias
• Kernel Function: @rbf_kernel
• Kernel Function Args = 0.9001
• GroupNames [781 x 1]
• Support Vector Indices [337 x 1]
• Scale Data containing:
  • shift [1 x 6]
  • scale factor [1 x 6]

These above are all data that I am able to load in python.

Now I would like to use this model in python without retraining to perform classification in python. In particular I would like to create a SVM model in python from the support vector generated in MATLAB

Is it possible? How? Any help would be very appreciated! I can't retrain it in python because I don't have the training data (and labels) anymore.

Answer 1

我想您了解SVM的工作原理，所以我要做的是再次在python上仅在找到的支持向量上训练模型，而不是在所有原始训练数据上训练，结果应该保持不变（就像您对SVM进行了训练一样）完整数据），因为支持向量是数据中位于边界上的“有趣”向量。