Hi, I am using one class svm for binary classification and was just curious what is the range/scale for sample weights? Are they normalized internally? For example -
Sample 1, weight - 1 Sample 2, weight - 10 Sample 3, weight - 100 Does this mean Sample 3 will always be predicted as positive and sample 1 will never be predicted as positive? What about sample 2? Also, what would happen if I assign a high weight to majority of the samples and low weights to the rest. Eg if 80% of my samples were weighted 1000 and 20% were weighted 1. A clarification or a link to read up on how exactly weights affect the training process would be really helpful. Thanks, Abhishek
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